Electronic device and method for acquiring metadata of image

Abstract

According to an embodiment, an electronic device may comprise: a display; at least one processor including a processing circuit; and a memory including one or more storage media for storing instructions. The instructions, when executed by the at least one processor, may cause the electronic device to acquire a single image. The instructions, when executed by the at least one processor, may cause the electronic device to, for a first area of the single image visually emphasized with respect to a second area of the single image, acquire map information for changing a gradation range of the first area from a first gradation range to a second gradation range from the single image when the single image is displayed. The instructions, when executed by the at least one processor, may cause the electronic device to store, in the memory, metadata including the map information. Various other embodiments are also possible.

Description

Electronic device and method for obtaining metadata of an image

[0001] The present disclosure relates to an electronic device and method for obtaining metadata of an image.

[0002] Digital information created to visualize images and / or videos (e.g., image files in the format of the Joint Photographic Experts Group (JPEG) and / or Moving Picture Experts Group (MPEG)) can be created to represent colors using a limited number of bits. For example, within the digital information, the brightness of a particular primary color (e.g., one of red, green, or blue) can be stored using eight bits. In the above example, the digital information has a total of 256 levels (= 2 8 ) can be generated to represent the brightness of a specific primary color using the brightness levels of the primary color.

[0003] The above information may be provided as background information to aid in understanding the present disclosure. None of the above is claimed to be prior art related to the present disclosure or can be used in making decisions related to prior art.

[0004] According to one embodiment, an electronic device may include a display, at least one processor including a processing circuit, and a memory including one or more storage media storing instructions. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to acquire a single image based on a predetermined event. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to acquire map information from the single image for changing a gradation range of the first region of the single image from a first gradation range to a second gradation range wider than the first gradation range, for a first region of the single image that is visually emphasized relative to a second region of the single image when the single image is displayed. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to store, in the memory, metadata including the map information and a file including the single image.

[0005] According to one embodiment, a method performed in an electronic device including a display may include an operation of acquiring a single image based on a predetermined event. The method may include an operation of acquiring, from the single image, map information for changing a gradation range of the first region from a first gradation range to a second gradation range wider than the first gradation range, for a first region of the single image that is visually emphasized with respect to a second region of the single image, when the single image is displayed. The method may include an operation of storing, in the memory, metadata including the map information and a file including the single image.

[0006] According to one embodiment, a non-transitory computer-readable storage medium may store one or more programs. The one or more programs may include instructions that, when executed by a processor of an electronic device, cause the electronic device to acquire a single image based on a predetermined event. The one or more programs may include instructions that, when executed by the processor of the electronic device, cause the electronic device to acquire map information from the single image for changing a gradation range of the first region of the single image from a first gradation range to a second gradation range wider than the first gradation range, for a first region of the single image that is visually emphasized relative to a second region of the single image, when the single image is displayed. The one or more programs may include instructions that, when executed by the processor of the electronic device, cause the electronic device to store, in the memory, metadata including the map information and a file including the single image.

[0007] FIG. 1 illustrates an example of the operation of an electronic device for displaying a screen from a single image, according to one embodiment.

[0008] FIG. 2 illustrates a block diagram of an electronic device according to one embodiment.

[0009] FIG. 3 illustrates a flowchart of the operation of an electronic device according to one embodiment.

[0010] FIG. 4 illustrates an example of operation of an electronic device for distinguishing a first region and a second region, according to one embodiment.

[0011] FIG. 5 illustrates an exemplary structure of a file generated by an electronic device according to one embodiment.

[0012] FIG. 6 illustrates an example of operation of an electronic device for obtaining map information, according to one embodiment.

[0013] FIG. 7A illustrates an example of operation of an electronic device for performing a flattening process, according to one embodiment.

[0014] FIG. 7b illustrates an example of specific operations of an electronic device for performing a flattening process, according to one embodiment.

[0015] FIG. 7c illustrates an example in which a gain image changes according to a flattening process, according to one embodiment.

[0016] FIG. 8 illustrates an example of specific operations of an electronic device for performing a filtering process according to one embodiment.

[0017] FIG. 9A illustrates an example of specific operations of an electronic device for performing a grayscale range setting process according to one embodiment.

[0018] FIG. 9b illustrates an example of changes in an image according to a grayscale range setting process, according to one embodiment.

[0019] FIG. 10A illustrates an example of operation of an electronic device for changing a grayscale range, according to one embodiment.

[0020] FIG. 10b illustrates an example of a change in an image according to a change in the tonal range, according to one embodiment.

[0021] FIG. 10c illustrates an example of an image change according to a change in the grayscale range, according to one embodiment.

[0022] FIG. 11 is a block diagram of an electronic device within a network environment according to various embodiments.

[0023] FIG. 12 is a block diagram illustrating a camera module according to various embodiments.

[0024] FIG. 13 is a block diagram of a display module according to various embodiments.

[0025] Hereinafter, various embodiments of this document are described with reference to the attached drawings.

[0026] The various embodiments of this document and the terminology used therein are not intended to limit the technology described in this document to a specific embodiment, but should be understood to include various modifications, equivalents, and / or substitutes of the embodiment. In connection with the description of the drawings, similar reference numerals may be used for similar components. The singular expression may include plural expressions unless the context clearly indicates otherwise. In this document, expressions such as "A or B", "at least one of A and / or B", "A, B, or C", or "at least one of A, B, and / or C" may include all possible combinations of the items listed together. Expressions such as "first", "second", "first", or "second" may modify the corresponding components regardless of order or importance, and are only used to distinguish one component from another, but do not limit the corresponding components. When it is said that a component (e.g., a first component) is “(functionally or communicatively) connected” or “connected” to another component (e.g., a second component), said component may be directly connected to said other component, or may be connected via another component (e.g., a third component).

[0027] The term "module" as used in this document includes a unit composed of hardware or firmware, and may be used interchangeably with terms such as logic, block, component, or circuit. A module may be an integral component, or a minimal unit or portion thereof that performs one or more functions. For example, a module may be composed of an application-specific integrated circuit (ASIC).

[0028] FIG. 1 illustrates an example of the operation of an electronic device for displaying a screen from a single image, according to one embodiment.

[0029] Referring to FIG. 1, the electronic device (101) may have various form factors, such as a smartphone, a laptop PC (personal computer), a tablet PC, a head-mounted display (HMD) device, a watch, and other similar computing devices (not shown). The electronic device (101) may also be referred to as a mobile device, a user terminal, a user equipment (UE), a multi-function device, a portable communication device, and / or a portable device. The form factor of the electronic device (101) is not limited to the exemplary form factors illustrated in FIG. 1.

[0030] In one embodiment, the electronic device (101) may generate a file (110), and / or visualize or display media content (e.g., media content referred to as a photograph and / or image) of the generated file (110). The file (110) may include a JPEG file, a high efficiency image file format (HEIF) file, a high efficiency image container (HEIC) file, a portable network graphic (PNG) file, and / or a graphics interchange format (GIF) file. An exemplary hardware configuration of the electronic device (101) for executing functions related to generating and / or processing the file (110) is described with reference to FIG. 2.

[0031] In the present disclosure, luminance may mean the intensity of light emitted from pixels of a display (120) (e.g., nit (or cd / m 2) of light intensity measured in units of light). In the present disclosure, the brightness value of the display (120) may refer to the brightness (or luminance) provided by the display (120). The brightness value of the display (120) and the brightness value of the image may be distinguished. In the present disclosure, the brightness value (or luma value, brightness level, gray scale value) of the image may refer to a relative value represented according to a specified number of bit depths, referred to as a brightness level, as a digital value assigned to a pixel of the image. For example, the brightness value of the image may include a Y value (or gray scale value) in a YUV color space.

[0032] In the present disclosure, the dynamic range of an image may mean the range of brightness of pixels of the image. Each pixel of an image having a standard dynamic range (SDR) uses a bit depth of 8 bits, and has 256 levels (= 2 8 ) can have any one of the brightness levels. For example, when displaying an image having SDR, the electronic device (101) can control the display (120) using the brightness values ​​(or luma values) of the pixels of the image. For example, the electronic device (101) can control the display (120) so that each pixel of the display (120) outputs light having any one of the brightness levels corresponding to the brightness levels of the 256 steps. SDR can express, for example, a color of the sRGB (standard RGB) color space. When displaying an image having SDR, the ratio between the minimum brightness and the maximum brightness of the pixels of the display (120) (hereinafter, contrast ratio) can be about 250: 1 (or about 256: 1). The minimum brightness and the maximum brightness can have a difference of about 100 nit.

[0033] According to one embodiment, the electronic device (101) may perform an operation related to a wider dynamic range than SDR (e.g., high dynamic range (HDR)). For example, the electronic device (101) may control the display (120) supporting HDR mode to change the contrast ratio of the display (120) to a contrast ratio exceeding the aforementioned 250:1 (e.g., 1,000:1, 10,000:1, and / or 20,000:1). For example, when the display (120) operates in HDR mode, the difference in brightness between pixels in dark and bright portions of an image displayed through the display (120) may increase.

[0034] Referring to FIG. 1, an electronic device (101) may acquire a first image (130). For example, the first image (130) may be a single image. The first image (130) may be referred to as a single image. The first image (130) may be acquired based on a predetermined event.

[0035] For example, the predetermined event may include an event for acquiring a plurality of images using at least one camera of the electronic device (101). The predetermined event may include an input for photographing an external environment using at least one camera. The first image (130) may be acquired based on the plurality of images acquired through the at least one camera. The plurality of images may have different exposure values. Each of the plurality of images may have a different dynamic range. The electronic device (101) may acquire (or generate) the first image (130) having a grayscale range with respect to SDR by synthesizing (e.g., bracketing) the plurality of images. For example, the first image (130) may include brightness values ​​represented according to a bit depth of 8 bits. As an example, the grayscale range of the first image (130) may mean a range of brightness values ​​of the first image (130) represented according to a bit depth of 8 bits. The grayscale range of the first image (130) may refer to a range for displaying brightness values ​​of pixels of the first image (130) represented according to a bit depth of 8 bits. For example, each brightness value of the pixels of the first image (130) may correspond to any one of 256 brightness levels. The grayscale range of the first image (130) may be set from the brightest first level among the brightness levels of the pixels of the first image (130) to the darkest second level among the brightness levels of the pixels of the first image (130). According to an embodiment, the predetermined event may include a user input for displaying the first image (130) through the display (120).

[0036] According to one embodiment, the electronic device (101) can identify the configuration information of the first image (130). The electronic device (101) can identify the first region (131) and the second region (132) based on the configuration information of the first image (130). For example, the configuration information of the first image (130) can include information about at least one camera for acquiring the first image (130), a shooting mode of the first image (130), or information about at least one object included in the first image (130).

[0037] The electronic device (101) can determine at least one grayscale level based on the setting information of the first image (130). The at least one grayscale level can be used to distinguish a first region (131) and a second region (132). The first region can have a first grayscale range. The second region can have a third grayscale range that is distinct from the first grayscale range. An example of the operation of the electronic device (101) to distinguish the first region (131) and the second region (132) based on at least one grayscale level will be described below with reference to FIG. 4.

[0038] The electronic device (101) can obtain map information (140) based on removing the second region (132) (or brightness values ​​of the second region (132) or data of the second region (132)) from the first image (130). For example, the map information (140) can be used to change the first grayscale range of the first region (131) to a second grayscale range wider than the first grayscale range. The electronic device (101) can store a file (110) including the first image (130) and the map information (140) in the memory of the electronic device (101). For example, the map information (140) can be referred to as a gain map. For example, the first image (130) can be configured based on a bit depth of 8 bits. The map information (140) can also be configured based on a bit depth of 8 bits. The operation of the electronic device (101) for obtaining map information (140) will be described later in the drawings described below.

[0039] The electronic device (101) can obtain (or configure) a second image (180) based on a file (110) including the first image (130) and map information (140) to display the first image (130) on the screen. The electronic device (101) can obtain the second image (180) based on the first image (130) and map information (140). The second image (180) can include a third area (181) corresponding to the first area (131) and a fourth area (182) corresponding to the second area (132).

[0040] The third area (181) of the second image (180) may be set brighter than the first area (131) of the first image (130). The fourth area (182) of the second image (180) may be set darker than the second area (132) of the first image (130). The electronic device (101) may identify the brightness value of the display (120) based on the first image (130) and the map information (140). In order to display the first image (130), the electronic device (101) may use the display (120) that provides brightness according to the identified brightness value to display the second image (180) configured based on the first image (130) and the map information (140).

[0041] For example, the fourth area (182) of the second image (180) may be set to be darker than the second area (132) of the first image (130). If the fourth area (182) of the second image (180) is displayed to be darker than the second area (132) of the first image (130), the user may feel a sense of incongruity. Accordingly, the electronic device (101) may identify a brightness value of the display (120) in which the brightness of the fourth area (182) of the second image (180) is set to be the same as or similar to the brightness of the second area (132) of the first image (130). The electronic device (101) may increase the brightness value of the display (120) so that the brightness of the fourth area (182) of the second image (180) is the same as or similar to the brightness of the second area (132) of the first image (130). As the brightness value of the display (120) increases, the third area (181) of the second image (180) may become brighter. Accordingly, the user of the electronic device (101) may perceive that the second area (132) of the first image (130) is maintained and the first area (131) of the first image (130) is displayed brighter.

[0042] In the following specification, an operation of an electronic device (101) for obtaining map information (140) for changing a grayscale range of a first area (131) from a first grayscale range to a second grayscale range wider than the first grayscale range from a first image (130) will be described.

[0043] FIG. 2 illustrates a block diagram of an electronic device according to one embodiment.

[0044] Referring to FIG. 2, the electronic device (101) may include a processor (210) (e.g., processor (1120) of FIG. 11), a display (120), a memory (215), and at least one camera (225). The hardware configuration of the electronic device (101) is not limited to the embodiment of FIG. 2. For example, the electronic device (101) may further include electronic components described with reference to FIG. 11. For example, some of the electronic components of FIG. 2 (e.g., at least one camera (225)) may be excluded from the electronic device (101).

[0045] For example, the processor (210) may be operably coupled with the display (120) or the display driver circuit (122) within the display (120). For example, the processor (210) being operably coupled with the display (120) (or the display driver circuit (122)) may indicate that the processor (210) is directly connected to the display (120) (or the display driver circuit (122)). For example, the processor (210) being operably coupled with the display (120) (or the display driver circuit (122)) may indicate that the processor (210) is connected to the display (120) (or the display driver circuit (122)) via another component of the electronic device (101). For example, the fact that the processor (210) is operatively coupled with the display (120) (or the display driving circuit (122)) may indicate that the state of the processor (210) is such that it can control the display (120) (or the display driving circuit (122)). For example, the fact that the processor (210) is operatively coupled with the display (120) (or the display driving circuit (122)) may indicate that the operation of the display (120) (or the display driving circuit (122)) is caused based on information, data, signals, or commands obtained from the processor (210). However, the present invention is not limited thereto.

[0046] For example, the processor (210) of the electronic device (101) may include a circuit (e.g., a processing circuit) for processing data based on one or more instructions. The circuit for processing data may include, for example, an arithmetic and logic unit (ALU), a floating point unit (FPU), a field programmable gate array (FPGA), a central processing unit (CPU), a graphics processing unit (GPU), a neural processing unit (NPU), and / or an application processor (AP). For example, the number of processors may be one or more. The processing circuit of the processor that loads (or fetches) instructions and performs calculations corresponding to the loaded instructions may be referred to as or referred to as a core circuit (or core). For example, the processor may have a multi-core processor structure including a plurality of core circuits, such as a dual core, a quad core, a hexa core, or an octa core. The functions and / or operations described with reference to the present disclosure may be performed individually or collectively by one or more processing circuits included in the processor (210).

[0047] For example, the display (120) of the electronic device (101) can output visualized information (e.g., a screen) to the user. For example, the display (120) can be controlled by a controller such as a GPU (graphics processing unit) to output visualized information to the user. The display (120) can include a liquid crystal display (LCD), a plasma display panel (PDP), and / or one or more light emitting diodes (LEDs). The LEDs can include organic LEDs (OLEDs). The display (120) can include a flat panel display (FPD) and / or electronic paper. The embodiment is not limited thereto, and the display (120) can have an at least partially curved shape or a deformable shape. A display (120) having a deformable shape can be referred to as a flexible display.

[0048] For example, the display (120) of the electronic device (101) may include a sensor (e.g., a touch sensor panel (TSP)) for detecting an external object (e.g., a user's finger) on the display (120). For example, based on the TSP, the processor (210) may detect an external object that is in contact with the display (120) or floating on the display (120). In response to detecting the external object, the processor (210) may execute a function related to a specific visual object corresponding to a location of the external object on the display (120) among visual objects displayed on the display (120).

[0049] For example, the display (120) may include a display driver circuit (122) (e.g., a display driver IC (1330) of FIG. 13) and a display panel (124) (e.g., a display (1310) of FIG. 13). For example, the display driver circuit (122) may be operatively coupled to the display panel (124). For example, when the display panel (124) includes a plurality of LEDs arranged in a two-dimensional matrix form, the display driver circuit (122) may be configured to control at least one LED included in a corresponding row or column among the plurality of LEDs. The display driver circuit (122) controlling the at least one LED may include an operation of adjusting the luminance (or light quantity, brightness) of the LEDs. In the present disclosure, luminance may mean the intensity of light emitted from pixels of the display (120) (e.g., nit (or cd / m 2 ) of light intensity measured in units of luminance). For example, the brightness value of the display (120) may mean the maximum value of luminance.

[0050] For example, the memory (215) of the electronic device (101) may include a circuit and / or a storage medium for storing data and / or instructions input and / or output to the processor (210). The memory (215) may include, for example, volatile memory such as random-access memory (RAM) and / or non-volatile memory such as read-only memory (ROM). The non-volatile memory may be referred to as storage. The volatile memory may include, for example, at least one of dynamic RAM (DRAM), static RAM (SRAM), cache RAM, and pseudo SRAM (PSRAM). The non-volatile memory may include, for example, at least one of programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), flash memory, hard disk, compact disc, solid state drive (SSD), and embedded multi media card (eMMC). The processor (210) of the electronic device (101) can execute instructions of the memory (215) within the electronic device (101) to perform functions and / or operations indicated by the instructions. For example, when the electronic device (101) includes at least one processor, the at least one processor can be configured to collectively or individually execute the instructions.

[0051] For example, at least one camera (225) of the electronic device (101) may include one or more optical sensors (e.g., a charged coupled device (CCD) sensor, a complementary metal oxide semiconductor (CMOS) sensor) that generate an electrical signal representing the color and / or brightness of light. The plurality of optical sensors included in the at least one camera (225) may be arranged in the form of a two-dimensional array. The at least one camera (225) may acquire the electrical signals of each of the plurality of optical sensors substantially simultaneously to generate two-dimensional frame data corresponding to light reaching the optical sensors of the two-dimensional array. For example, photographic data captured using the at least one camera (225) may mean one (a) two-dimensional frame data acquired from the at least one camera (225). For example, video data captured using the at least one camera (225) may mean a sequence of a plurality of two-dimensional frame data acquired from the at least one camera (225). At least one camera (225) of FIG. 2 may include a camera module (1180) of FIG. 11 and / or FIG. 12.

[0052] Referring to FIG. 2, information (e.g., a file (110)) and / or programs (e.g., an image renderer (216) and / or a display brightness determiner (217)) stored in a memory (215) of an electronic device (101) are illustrated. A processor (210) that executes instructions included in a program may perform functions and / or operations indicated by the instructions. The file (110) may include color information representing the colors of pixels of an image (e.g., the first image (130) of FIG. 1) according to a color space such as YUV, RGB, and / or HSV. For example, a file (110) based on a color space of RGB may represent the color of a specific pixel using the intensities of the three primary colors of red, green, and blue. For example, a file (110) based on the color space of YUV can represent the color of a specific pixel using three components including a brightness component (e.g., Y component) and chrominance components (e.g., Cb component, and / or Cr component).

[0053] For example, at least three channels can be used to represent the colors of pixels of an image. From a file (110) in JPEG format, the processor (210) can identify the colors of a plurality of pixels expressed by three channels having a bit depth of 8 bits. The file (110) can additionally include map information (e.g., map information (140) of FIG. 1) corresponding to a specific component (e.g., brightness component). The map information corresponding to a specific component can be used to increase the bit depth of the specific component (e.g., to a bit depth greater than 8 bits).

[0054] By executing the image renderer (216), the processor (210) can generate or synthesize an image having an HDR effect (e.g., a second image (180) of FIG. 1) from an image having an SDR included in the file (110) (e.g., a first image (130) of FIG. 1). For example, the processor (210) can restore an image having an HDR effect from an image of an SDR using map information (e.g., a map information (140) of FIG. 1) included in the metadata of the file (110). The restoration can include scaling (e.g., amplifying and / or attenuating) the brightness of pixels of the image of the SDR using information included in the map information. The processor (210) executing the image renderer (216) can generate or obtain information for displaying an image having a contrast ratio of HDR.

[0055] By executing the display brightness determiner (217), the processor (210) can increase, at least partially, the brightness of the pixels of the display (120). The processor (210) executing the display brightness determiner (217) can control the display driving circuit (122) to increase, at least partially, the brightness of the display (120). For example, in order to visually emphasize a portion of an image to be displayed on the display (120) over another portion, the processor (210) can cause the brightness of at least one pixel of the display (120) corresponding to the portion to exceed the brightness of at least one pixel of the display (120) corresponding to the other portion. For example, the processor (210) may set the brightness of at least one pixel of the display (120) corresponding to a portion of an image to be displayed on the display (120) (e.g., a portion to be highlighted or the first area (131) of FIG. 1) to be brighter than the brightness of at least one pixel of the display (120) corresponding to another portion of the image (e.g., a portion excluding the portion to be highlighted or the second area (132) of FIG. 1).

[0056] The processor (210) that executes the display brightness determiner (217) can adjust the gamma of the image rendered by the image renderer (216). The gamma may refer to the relationship between the brightness of the pixels of the image and the brightness of the pixels of the display (120) that displays the image. The gamma may be expressed as a function referred to as a gamma curve. When displaying an image synthesized from a file (110) (e.g., the second image (180) of FIG. 1), the processor (210) may control the display driving circuit (122) to display the image using the gamma related to the metadata (e.g., map information (140)) of the file (110).

[0057] Figure 3 illustrates a flowchart of the operation of an electronic device according to one embodiment. In the following embodiments, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0058] Referring to FIG. 3, in operation 310, the processor (210) may acquire a single image (e.g., the first image (130) of FIG. 1). For example, the processor (210) may acquire the single image based on a predetermined event.

[0059] For example, the predetermined event may include an event for acquiring a plurality of images using at least one camera (225) of the electronic device (101). The predetermined event may include an input for capturing an external environment using at least one camera (225). A single image may be acquired based on the plurality of images. Each of the plurality of images may have a different dynamic range. The electronic device (101) may acquire (or generate) a single image having a grayscale range with respect to SDR by synthesizing (e.g., bracketing) the plurality of images.

[0060] For example, the predetermined event may include an event for acquiring a single image with a single exposure value using a single camera. For example, the processor (210) may apply a tone mapping operator (TMO) to a Bayer pattern before performing 8-bit image signal processing (ISP). The processor (210) may map grayscale to maximize the dynamic range of the single image and, if the brightness of the subject area is different, to distinguish and express it. The processor (210) may acquire a single image according to the example described above. According to an embodiment, the predetermined event may include a user input for displaying the single image on the display (120).

[0061] For example, a single image may be composed based on a bit depth of 8 bits. The single image may include brightness values ​​represented according to the bit depth of 8 bits. The grayscale range of the single image may mean the range of brightness values ​​of the single image represented according to the bit depth of 8 bits. The grayscale range of the single image may be set from the brightest first level among the brightness levels of the pixels of the single image to the darkest second level among the brightness levels of the pixels of the single image.

[0062] In operation 320, the processor (210) may obtain map information for changing the grayscale range of the first region from the first grayscale range to the second grayscale range when the single image is displayed, for a first region of the single image that is visually emphasized with respect to a second region of the single image. For example, the second grayscale range may be wider than the first grayscale range.

[0063] According to one embodiment, the processor (210) can distinguish a first region and a second region in a single image. For example, the processor (210) can determine at least one grayscale level based on configuration information regarding the single image. The processor (210) can identify the first region and the second region within the single image based on the at least one grayscale level. The at least one grayscale level can be used to distinguish the first region and the second region.

[0064] For example, the setting information regarding a single image may include at least one of information regarding at least one camera (225) for acquiring the single image, a shooting mode regarding the single image (e.g., a portrait shooting mode, a food shooting mode, a night scene shooting mode, or a text shooting mode), or information regarding at least one object included in the single image. According to an embodiment, the processor (210) may determine at least one grayscale level based on not only the setting information regarding the single image, but also capability information (or setting information) of the display (120) and / or capability information (or setting information) of at least one camera (225).

[0065] For example, at least one grayscale level may include a threshold grayscale level. The processor (210) may identify a grayscale range exceeding the threshold grayscale level as a first grayscale range. The first region may have a grayscale range exceeding the threshold grayscale level (or a first grayscale range). The second region may have a grayscale range below the threshold grayscale level (or a third grayscale range).

[0066] For example, the first region may be referred to as a high-luminance region. The second region may be referred to as a low-luminance region. For example, the first region may be referred to as an HDR region. The second region may be referred to as an SDR region.

[0067] According to one embodiment, the processor (210) may obtain a gain image including a first region by removing a second region (or brightness values ​​of the second region or data of the second region) from a single image. The processor (210) may obtain map information based on the gain image. The processor (210) may obtain the map information based on the gain image using a designated algorithm and / or a designated filter. For example, the processor (210) may remove distortion of the gain image using a designated algorithm and / or a designated filter. The processor (210) may obtain map information based on removing distortion of the gain image. The map information may be a gain image corrected using a designated algorithm and / or a designated filter. An example of an operation of the processor (210) for obtaining map information based on the gain image using a designated algorithm and / or a designated filter will be described below with reference to FIGS. 6 to 9B. According to an embodiment, the gain image may correspond to the map information. For example, the map information may be a gain image.

[0068] For example, the map information may be used to change the grayscale range of the first region to a second grayscale range that is wider than the first grayscale range. The processor (210) may configure another image based on a single image and the map information. For example, when the grayscale range of the first region is changed from the first grayscale range to the second grayscale range, the brightness values ​​of at least some of the pixels included in the first region may increase. The processor (210) may obtain the map information to change the grayscale range of the first region from a first grayscale range of 30 to 200 to a second grayscale range of 30 to 250.

[0069] According to one embodiment, the processor (210) can identify that a specified object (e.g., a face of a person (or a user)) is included in a single image. The processor (210) can reduce the second grayscale range based on identifying that a specified object (e.g., a face of a person (or a user)) is included in the single image. The processor (210) can obtain map information for changing the grayscale range of the first region from the first grayscale range to the reduced second grayscale range.

[0070] In operation 330, the processor (210) may store a file (e.g., file (110) of FIG. 1) containing metadata including map information and a single image. For example, a specific example of a file containing metadata and a single image will be described later in FIG. 5.

[0071] In one embodiment, the processor (210) may display a single image on the display (120) based on a file containing metadata including map information and a single image. For example, the processor (210) may identify a brightness value of the display (120) based on the metadata and the single image. To display the single image, the processor (210) may use the display (120) to provide brightness according to the identified brightness value, and display another image configured based on the metadata and the single image.

[0072] For example, the processor (210) can identify a user input for displaying a single image. The processor (210) can compose another image based on the single image and metadata. The processor (210) can identify a brightness value of the display (120) based on the single image and metadata. The processor (210) can display another image using the display (120) that provides brightness according to the identified brightness value. By displaying the other image, the processor (210) can highlight a first area of ​​the single image and provide it to the user. The user of the electronic device (101) can recognize (or identify) the other image in which the first area of ​​the single image is highlighted compared to the single image.

[0073] FIG. 4 illustrates an example of operation of an electronic device for distinguishing a first region and a second region, according to one embodiment.

[0074] Referring to FIG. 4, the graph (401) represents a normalized luminance level according to a normalized grayscale level for the first image (130). The graph (402) represents a normalized luminance level according to a normalized grayscale level for the second image (180).

[0075] The processor (210) can identify a threshold grayscale level (410). For example, the processor (210) can identify setting information of the first image (130). The processor (210) can identify the threshold grayscale level (410) based on the setting information of the first image (130). The processor (210) can identify a first region (131) and a second region (132) based on the threshold grayscale level (410). The processor (210) can divide the first image (130) into a first region (131) and a second region (132) based on the threshold grayscale level (410).

[0076] For example, the threshold grayscale level (410) can be set to a grayscale level at which a contour does not occur when the second image (180) is displayed on the display (120).

[0077] For example, the processor (210) can identify a threshold luminance level (420) according to a threshold gradation level (410). Based on the threshold luminance level (420), the processor (210) can identify a first region (131) and a second region (132). Based on the threshold luminance level (420), the processor (210) can divide the first image (130) into a first region (131) and a second region (132).

[0078] In FIG. 4, an example is shown in which a first region (131) and a second region (132) are distinguished based on a threshold grayscale level (410), but the present invention is not limited thereto. The processor (210) may identify a plurality of threshold grayscale levels. For example, the processor (210) may identify a first threshold grayscale level and a second threshold grayscale level. The processor (210) may identify a first region having a grayscale range between the first threshold grayscale level and the second threshold grayscale level. The processor (210) may also identify an area remaining except for the first region as a second region. The processor (210) may set the first region based on the characteristics of the first image (130) (or the characteristics of at least one visual object included in the first image (130).

[0079] According to one embodiment, the processor (210) may distinguish a first region (131) and a second region (132) to obtain map information. The processor (210) may obtain a gain image (121) from which the second region (132) is excluded from the first image (130). The processor (210) may obtain map information (140) based on the gain image (121). The processor (210) may obtain a second image (180) based on the first image (130) and the map information (140). The processor (210) may change the grayscale range of the first region (131) of the first image (130) from the first grayscale range to a second grayscale range wider than the first grayscale range. The processor (210) can obtain a second image (180) in which the grayscale range of the first area (131) is changed from the first grayscale range to the second grayscale range. The processor (210) can display the second image (180) using the display (120).

[0080] For example, the first image (130) may be configured based on a bit depth of 8 bits. The gain image (121) (or map information (140)) may also be configured based on a bit depth of 8 bits. The second image (180) may also be configured based on a bit depth of 8 bits. As an example, the processor (210) may obtain the second image (180) configured based on a bit depth of 8 bits by using the first image (130) configured based on a bit depth of 8 bits and the map information (140) configured based on a bit depth of 8 bits. The processor (210) may compress (or reduce) the bit depth of the first image (130) from 8 bits to 7 bits. The processor (210) may compress (or reduce) the bit depth of the map information (140) from 8 bits to 7 bits. The processor (210) can obtain a second image (180) configured based on a bit depth of 8 bits by performing a combination of the first image (130) and map information (140).

[0081] For example, the second image (180) displayed through the display (120) may include a third region (181) and a fourth region (182). The third region (181) of the second image (180) may correspond to the first region (131) of the first image (130). The fourth region (182) of the second image (180) may correspond to the second region (132) of the first image (130). The fourth region (182) of the second image (180) displayed through the display (120) may be displayed identically or similarly to the second region (132) of the first image (130). The third region (181) of the second image (180) displayed through the display (120) may be visually emphasized more than the first region (131) of the first image (130).

[0082] For example, the luminance level for the third region (181) of the second image (180) may be set to be greater than the luminance level for the first region (131) of the first image (130). The processor (210) may change the grayscale range of the first region to a second grayscale range wider than the first grayscale range by combining the first image (130) and the map information (140). As the grayscale range of the first region (131) is changed to the second grayscale range, the luminance level for the third region (181) of the second image (180) may be set to be greater than the luminance level for the first region (131) of the first image (130). Accordingly, the processor (210) may display the second image (180) through the display (120) in which the first region (131) of the first image (130) is visually emphasized relative to the second region (132).

[0083] According to one embodiment, in the first image (130), when the normalized grayscale level is '1' (or the grayscale level is 255), the brightness value (or luminance) of the display (120) may be set to 300 nit. In the second image (180), when the normalized grayscale level is '1' (or the grayscale level is 255), the brightness value (or luminance) of the display (120) may be set to 360 nit. Graphs (401) and (402) are exemplary and are not limited thereto. Graph (402) may be changed according to setting information (or user settings, settings of the display (120)). For example, in the first image (130), when the normalized grayscale level is '1' (or the grayscale level is 255), the brightness value (or luminance) of the display (120) may be set to 300 nit. In the second image (180), when the normalized grayscale level is '1' (or the grayscale level is 255), the brightness value (or luminance) of the display (120) may be set to 2000 nit.

[0084] For example, in the first image (130), if the normalized grayscale level is '1', the normalized luminance level of the display (120) may be set to '1'. In the second image (180), if the normalized grayscale level is '1', the normalized luminance level of the display (120) may be set to '1.2'. As the second image (180) is displayed through the display (120) instead of the first image (130), the luminance level may be changed from '1' to '1.2'. The rate at which the luminance level is changed may be changed depending on the embodiment. The rate at which the luminance level is changed may be referred to as the SDR-to-HDR ratio.

[0085] According to one embodiment, the grayscale range of the first region (131) can be rearranged through a gamma curve. For example, the gamma curve can include a hybrid log gamma (HLG) curve and / or a perceptual quantization (PQ) curve. According to an embodiment, the processor (210) can set the gamma curve applied to the first grayscale range of the first region (131) to be different from the gamma curve applied to the third grayscale range of the second region (132).

[0086] According to the above-described embodiment, the processor (210) can restore the second image (180), which is an image having an HDR effect, by rearranging the luminance information arranged in the first image (130), which is an SDR image, through TMO. The processor (210) can store the first region (131), which is a high-luminance region included in the first image (130), as map information (140). Using the map information (140), the processor (210) can display the third region (181), which corresponds to the first region (131), by mapping it to high luminance through the display (120).

[0087] FIG. 5 illustrates an exemplary structure of a file generated by an electronic device according to one embodiment.

[0088] Referring to FIG. 5, the structure of a file (110) based on the format of the International Standardization Organization (ISO), referred to as EXIF ​​(EXchangeable Image File), is illustrated. The file (110) stored in a memory (e.g., memory (215) of FIG. 2) may start from an area (M1) in which a designated value (e.g., a value of Table 1 below) indicating the start of the file (110) is stored. After the area (M1), application areas (Application segments, APP) (e.g., M2, M3, M4, ..., M10) may be formed within the file (110).

[0089] Tag information may be stored in the first application area (M2) of the file (110). The tag information may include one or more character strings used for indexing the file (110). Content list data (M3) and / or stream data (M4 to M10) may be stored in the second application area (APP2) of the file (110). Within the file (110), after the application areas (M2, M3, ..., M10), a JPEG table area (M11, M12, ..., M15) may be formed. The JPEG table area may include a DQT (Define-Quantization-Tables) area (M11) (e.g., a variable area starting with a value in Table 1 below), a DHT (Define-Huffman-Tables) area (M12) (e.g., a variable area starting with a value in Table 1 below), a DRI (Define-Restart-Interval) area (M13) (e.g., a fixed area starting with a value in Table 1 below), a SOF (Start Of Frame) area (M14), and / or a SOS (Start-Of-Scan) area (M15) (e.g., a variable area starting with a value in Table 1 below). Within the file (110), a JPEG compressed data area (M16) may be formed after the JPEG table area. The file (110) may include, after the JPEG compressed data area (M16), an area (M17) in which a designated value is stored to indicate the end of the file (110) (e.g., a fixed area starting with the value in Table 1 below).

[0090] In one embodiment, information stored in a file (110) based on the format of EXIF ​​is not limited to the example of FIG. 5. For example, the file (110) may include information having a name in Table 1.

[0091] Abbreviation file (110) Value (hexadecimal based) Length of information (or payload) Name SOI 0xFF, 0xD8 None Start point of image SOF 00xFF, 0xC0 Variable Start point of frame (baseline DCT (discrete cosine transform)) SOF 2 0xFF, 0xC2 Variable Start point of frame (progressive DCT) DHT 0xFF, 0xC4 Variable Definition of Huffman table DQT 0xFF, 0xDB Variable Definition of quantization table DRI 0xFF, 0xDD4 Definition of byte restart period SOS 0xFF, 0xDA Variable Start point of scan RSTn 0xFF, 0xDn (n = 0, ..., 7) None Restart point APPn 0xFF, 0xEn Variable Application area (EXIF, APP1, etc.) COM 0xFF, 0xFE variable comment EOI 0xFF, 0xD9 none End point of image

[0092] According to one embodiment, a single image may be stored in a JPEG compressed data area (M16) within a file (110). For example, a first image (130) may be stored in a JPEG compressed data area (M16) within the file (110). Metadata may be stored in other areas (e.g., M2 to M10) of the file (110) that are different from the JPEG compressed data area (M16). For example, map information (140) used to restore and / or display an image with an HDR effect may be stored in a second application area (APP2) of the file (110).

[0093] Although not illustrated, in some embodiments, map information (140) may be stored in the metadata area of ​​an extensible metadata platform (XMP).

[0094] Below, an example of a specific operation of an electronic device (101) (or processor (210)) for obtaining metadata (e.g., map information) from a single image will be described.

[0095] FIG. 6 illustrates an example of operation of an electronic device for obtaining map information, according to one embodiment.

[0096] Referring to FIG. 6, the processor (210) can obtain map information (e.g., map information (140) of FIG. 1) using a single image (e.g., the first image (130) of FIG. 1). For example, the processor (210) can obtain map information using a single image by performing a gain image obtaining process (610), a flattening process (620), a filtering process (630), and / or a grayscale range correction process (640). The processor (210) can obtain map information for changing the grayscale range of a first area within the single image from a first grayscale range to a second grayscale range wider than the first grayscale range.

[0097] According to one embodiment, the processor (210) may perform a gain image acquisition process (610) using a single image. The processor (210) may distinguish a first region (e.g., a first region (131) of FIG. 1) and a second region (e.g., a second region (132) of FIG. 1) from the single image. For example, the processor (210) may determine at least one grayscale level based on setting information regarding the single image. The processor (210) may distinguish the first region and the second region within the single image based on the at least one grayscale level.

[0098] For example, the processor (210) can identify a threshold grayscale level included in at least one grayscale level. The processor (210) can identify a grayscale range exceeding the threshold grayscale level as a first grayscale range. The processor (210) can identify a grayscale range below the threshold grayscale level as a third grayscale range. The processor (210) can identify a first area having the first grayscale range. The processor (210) can identify a second area having the third grayscale range.

[0099] For example, the processor (210) can obtain a gain image by excluding a second region within a single image. The processor (210) can obtain a gain image having data for a first region within the single image. If operations 620 to 640 are not performed, the gain image can be referenced (or identified) with map information.

[0100] After the gain image is acquired, the processor (210) may perform a flattening process (620), a filtering process (630), and / or a grayscale range correction process (640). In FIG. 6, the flattening process (620), the filtering process (630), and the grayscale range correction process (640) are illustrated as being performed sequentially, but this is not limited thereto. The order in which the flattening process (620), the filtering process (630), and the grayscale range correction process (640) are performed may be changed. Depending on the embodiment, at least some of the flattening process (620), the filtering process (630), and the grayscale range correction process (640) may not be performed.

[0101] For convenience of explanation, the target image (or input image) for the flattening process (620), the filtering process (630), and the grayscale range correction process (640) will be described as a gain image. For example, if the filtering process (630) is performed after the flattening process (620), the target image for the filtering process (630) may be the gain image on which the flattening process (620) is performed. For example, if the grayscale range correction process (640) is performed after the flattening process (620), the target image for the flattening process (620) may be the gain image on which the grayscale range correction process (640) is performed.

[0102] According to one embodiment, the processor (210) may perform a smoothing process (620) using the gain image. For example, the processor (210) may remove distortion of at least one object included in the gain image using a specified algorithm. Specific examples of the smoothing process (620) will be described below with reference to FIGS. 7A to 7C .

[0103] According to one embodiment, the processor (210) may perform a filtering process (630) using a gain image. The processor (210) may apply a specified filter to the gain image. By applying the specified filter to the gain image, the processor (210) may remove distortion of at least one object included in the gain image while maintaining the outline of the at least one object. An example of the specific operation of the filtering process (630) will be described later in FIG. 8.

[0104] According to one embodiment, the processor (210) may perform a grayscale range setting process (640) using a gain image. The processor (210) may identify whether a specified object (e.g., a human face) is included within a single image.

[0105] The processor (210) may reduce the second tone range when a specified object (e.g., a human face) is included in a single image. The processor (210) may configure map information so that the second tone range is reduced. The reduced second tone range may be wider than the first tone range. The processor (210) may maintain the second tone range when a specified object is not included in a single image. The processor (210) may configure map information so that the second tone range is maintained. An example of a specific operation of the tone range setting process (640) will be described later with reference to FIGS. 9A and 9B .

[0106] According to the above-described embodiment, the processor (210) can obtain map information from a single image by performing at least one of a gain image acquisition process (610), a flattening process (620), a filtering process (630), and / or a grayscale range correction process (640). Based on the single image and the map information, the processor (210) can obtain (or compose) another image including a first region visually emphasized with respect to a second region. For example, the processor (210) can change the grayscale range of the first region from the first grayscale range to a second grayscale range wider than the first grayscale range. The processor (210) can obtain (or compose) another image by changing the grayscale range of the first region from the first grayscale range to a second grayscale range wider than the first grayscale range. Based on the single image and the map information, the processor (210) can identify a brightness value of the display (120). The processor (210) can display the other image using the display (120) that provides brightness according to the identified brightness value. By displaying the other image using the display (120) that provides brightness according to the identified brightness value, the processor (210) can visually emphasize a first area of ​​a single image relative to a second area.

[0107] FIG. 7A illustrates an example of operation of an electronic device for performing a flattening process, according to one embodiment.

[0108] FIG. 7b illustrates an example of specific operations of an electronic device for performing a flattening process, according to one embodiment.

[0109] FIG. 7c illustrates an example in which a gain image changes according to a flattening process, according to one embodiment.

[0110] Referring to FIG. 7A, since the gain image is acquired based on a threshold grayscale value, the gain image may include noise and / or distortion. The processor (210) can remove noise and / or distortion from the gain image by performing operations 710 to 730.

[0111] In operation 710, the processor (210) can obtain a first processed image based on reducing the brightness levels of the gain image.

[0112] In operation 720, the processor (210) may obtain a second processed image based on the correction performed on the first processed image. The processor (210) may obtain a second processed image by correcting the first processed image. A specific operation for obtaining the second processed image by correcting the first processed image will be described later in FIG. 8.

[0113] For example, the processor (210) may obtain a second processed image based on reducing and then enlarging the size of the first processed image. As the first processed image is reduced and then enlarged, at least some of the noise and / or distortion may be removed.

[0114] In operation 730, the processor (210) may remove distortion of at least one object included in the gain image based on increasing the brightness levels of the second processed image. The processor (210) may obtain map information with the distortion removed by increasing the brightness levels of the second processed image again. For example, if the brightness levels are reduced by 1 / 4 according to operation 710, the processor (210) may increase the brightness levels by a factor of four.

[0115] The processor (210) can obtain map information by removing distortion of at least one object included in the gain image according to operations 710 to 730. For example, operations 710 to 730 can be performed based on a designated algorithm. FIG. 8 will describe the operation of a designated algorithm for performing operations 710 to 730.

[0116] Referring to FIG. 7b, operations 721 to 726 may be examples of operation 720 of FIG. 7a.

[0117] In operation 710, the processor (210) may reduce the brightness levels of the gain image based on the gain image. The processor (210) may obtain a first processed image based on reducing the brightness levels of the gain image. Operation 710 may correspond to operation 710 of FIG. 7A.

[0118] In operation 721, the processor (210) may perform a binarization conversion on the first processed image. The processor (210) may set the brightness level to a first value (e.g., '1') based on whether the brightness level exceeds a specified brightness level. The processor (210) may set the brightness level to a second value (e.g., '0') based on whether the brightness level is less than or equal to the specified brightness level. The processor (210) may perform the binarization conversion by setting each of the brightness values ​​of the pixels of the first processed image to one of the first value and the second value.

[0119] At operation 722, the processor (210) may perform a morphology operation. The processor (210) may reduce noise (e.g., misidentified light sources) based on reducing and then increasing the size of the image on which operation 721 was performed. For example, the processor (210) may reduce noise (e.g., misidentified light sources) based on performing dilation and / or erosion of the image on which operation 721 was performed according to the morphology operation.

[0120] In operation 723, the processor (210) may perform a connected component operation. Based on performing the connected component operation, the processor (210) may set labels of objects within the image on which operation 722 was performed. Based on performing the connected component operation, the processor (210) may obtain a label map of objects included in the image on which operation 722 was performed. According to an embodiment, the processor (210) may perform correction on the label map. The processor (210) may perform correction on the label map based on an aspect ratio or size.

[0121] In operation 724, the processor (210) can identify a non-light source. The processor (210) can identify a non-light source based on statistical values ​​(e.g., average value or mean value) of labels included in the label map.

[0122] At step 725, the processor (210) may calibrate the brightness levels of each of the labels. For example, the processor (210) may identify a ceiling line (or maximum value) of the brightness levels of the labels included in the label map. The processor (210) may change the brightness levels of the labels to the ceiling line (or maximum value).

[0123] At operation 726, the processor (210) may apply a weight to the brightness levels of each of the labels. The processor (210) may apply the weight to the brightness levels of each of the labels based on at least one of flatness of the brightness levels of each of the labels, an average value of the brightness levels, and / or a grayscale variation. By performing operation 726, the processor (210) may obtain a second processed image.

[0124] In operation 730, the processor (210) may increase the brightness levels of the second processed image. By increasing the brightness levels of the second processed image again, the processor (210) may remove noise and / or distortion included in the gain image. Based on the removal of noise and / or distortion included in the gain image, the processor (210) may obtain map information.

[0125] Referring to FIG. 7c, the processor (210) may convert the image (751) into the image (752) based on a flattening process (e.g., the flattening process (620) of FIG. 6). For example, the image (751) may be an example of a gain image. The image (752) may be an example of map information.

[0126] The image (751) may include at least one object including an object (761). The object (761) may represent an external object (e.g., a fluorescent light). Even when the object (761) represents the same external object, the grayscale range of the object (761) may be configured to be wider than a specified grayscale range. If the grayscale range is wide, the object (761) may be displayed in a blotchy form. For example, the grayscale levels of a region (763) of the object (761) and the grayscale levels of a region (764) may be distinguished. If the grayscale levels of a region (763) and the grayscale levels of a region (764) are distinguished, the object (761) representing the same object may be displayed in a blotchy form. Therefore, the processor (210) may perform a smoothing process to narrow the grayscale range of the object (761).

[0127] The graph (770) represents the detection frequency according to the grayscale level of the object (761). The object (761) may have grayscale levels in the grayscale range (771). The processor (210) may perform a flattening process on the image (751). The processor (210) may obtain the image (752) based on the flattening process. For example, the processor (210) may obtain the image (752) by changing the object (761) to the object (762). The graph (780) represents the detection frequency according to the grayscale level of the object (762). The object (762) may have grayscale levels in the grayscale range (781). The grayscale range (781) may be narrower than the grayscale range (771).

[0128] The processor (210) can obtain an object (762) having identical or similar grayscale levels by narrowing the grayscale range of the object (761) through a flattening process. When the grayscale levels of the object (762) are configured identically or similarly, an object (762) representing the same object may not be displayed in a blotchy form.

[0129] According to the above-described embodiment, as the internal contrast of a highlight area (e.g., object (761)) increases, the user may perceive that spot distortion occurs in the highlight area. The processor (210) may perform smoothing so that the user does not perceive spot distortion by reducing the internal contrast of the highlight area.

[0130] FIG. 8 illustrates an example of specific operations of an electronic device for performing a filtering process according to one embodiment.

[0131] Referring to FIG. 8, in operation 810, the processor (210) may apply a specified filter to the gain image. For example, the processor (210) may apply a specified filter to the gain image to remove distortion of at least one object included in the gain image while maintaining an outline of the at least one object included in the gain image. For example, the specified filter may include a guided image filter (GIF). Based on applying the GIF to the gain image, the processor (210) may preserve an edge region of the gain image and flatten the remaining region. The processor (210) may remove sparkle distortion within the gain image while preserving an outline of a human face and / or an object.

[0132] In one embodiment, a portion of a reflector may be identified as a high-brightness region. For example, depending on the characteristics of the light source (e.g., intensity or direction) or the characteristics of the reflector (e.g., shape, size, material), a portion of the reflector may be identified as a high-brightness region. If a portion of the reflector is identified as a high-brightness region, the portion may be displayed as unnecessarily bright according to the gamma mapping process described in FIG. 4. For example, when a person's face is photographed outdoors, the face may be photographed brightly due to an outdoor light source (e.g., sunlight), and an area corresponding to the bridge of the nose may be identified as a high-brightness region. Therefore, the area may be identified as having sparkle distortion.

[0133] The processor (210) may apply a specified filter to the gain image when a portion of the reflector is identified as a high-brightness region. The processor (210) may remove sparkle distortion by applying the specified filter to the gain image. The processor (210) may remove sparkle distortion within the gain image while maintaining the outline or edge area of ​​the object corresponding to the semi-subject within the gain image.

[0134] In operation 820, the processor (210) may obtain map information. For example, the processor (210) may obtain map information based on a gain image to which a specified filter is applied. The gain image to which the specified filter is applied may be an image from which distortion (e.g., sparkle distortion) has been removed. The processor (120) may obtain a gain image from which distortion has been removed through the specified filter, and may obtain map information from which distortion has been removed using the obtained gain image.

[0135] FIG. 9A illustrates an example of specific operations of an electronic device for performing a grayscale range setting process according to one embodiment.

[0136] FIG. 9b illustrates an example of changes in an image according to a grayscale range setting process, according to one embodiment.

[0137] Referring to FIG. 9A, at operation 910, the processor (210) may identify whether a specified object is included within a single image. For example, the specified object may include a part of the user's body (e.g., a face), a specified object (e.g., food), or objects representing a specified scene.

[0138] The processor (210) may perform an object recognition process for at least one object included in a single image. For example, the processor (210) may perform an object recognition process for at least one object using a designated prediction model (e.g., an artificial intelligence model). The processor (210) may set at least one object as input data of the designated prediction model. The processor (210) may identify a type (or class) of at least one object based on output data of the designated prediction model. Based on identifying the type of at least one object, the processor (210) may identify whether a designated object is included in the single image.

[0139] In operation 920, if a specified object is included in a single image, the processor (210) may reduce the second grayscale range. For example, the processor (210) may reduce the second grayscale range based on identifying that a specified object is included in a single image. The processor (210) may configure map information such that the second grayscale range is reduced.

[0140] In operation 930, if a specified object is not included in a single image, the processor (210) may maintain a second tone range. For example, the processor (210) may maintain the second tone range based on identifying that a specified object is not included in a single image. The processor (210) may configure map information such that the second tone range is maintained.

[0141] According to operations 910 to 930, the processor (210) may determine whether to reduce the second tone range depending on whether a specified object is included in a single image. For example, a person's face may be included in the single image. If the overall brightness level of the person's face is set high, the brightness level of the person's face may increase further in another image configured based on the single image and map information. The person's face is the part that the user of the electronic device (101) is most sensitive to, and if the brightness change of the person's face is large, the user may feel a sense of incongruity. Therefore, if a person's face is included in the single image, the rate of increase in the brightness level of the single image may be reduced by reducing the second tone range.

[0142] Referring to FIG. 9B, the processor (210) can obtain an image (951). The image (951) may be an example of a single image described in FIG. 9A. The processor (210) can obtain images (952, 953) configured based on the image (951) and map information obtained from the image (951).

[0143] For example, image (952) may be an image obtained from map information configured to maintain the second tone range. Image (953) may be an image obtained from map information configured to reduce the second tone range.

[0144] According to one embodiment, the processor (210) may determine at least one grayscale level based on setting information regarding the image (951). The processor (210) may identify a first region and a second region based on the at least one grayscale level. The processor (210) may identify a region corresponding to a specified object (901) as a first region. The processor (210) may identify a region excluding the region corresponding to the specified object (901) as a second region.

[0145] The processor (210) may obtain map information to visually emphasize a first region (e.g., a region corresponding to a designated object (901)) relative to a second region. For example, the map information may be used to change the grayscale range of the first region from a first grayscale range to a second grayscale range that is wider than the first grayscale range.

[0146] According to one embodiment, the processor (210) may identify that a designated object (901) is included in an image (951). For example, the designated object (901) may represent a human face. The processor (210) may reduce a second grayscale range based on identifying that the designated object (901) is included in the image (951). The reduced second grayscale range may be wider than the first grayscale range. The processor (210) may obtain map information for changing a grayscale range of a first area (e.g., an area corresponding to the designated object (901)) from the first grayscale range to the reduced second grayscale range. The processor (210) may obtain an image (953) based on the image (951) and the map information. Brightness levels of the object (903) in the image (953) may be set to be greater than brightness levels of the object (901) in the image (951).

[0147] According to an embodiment, when the second tone range is maintained, the processor (210) may obtain map information for changing the tone range of a first area (e.g., an area corresponding to a designated object (901)) from the first tone range to the maintained second tone range. The processor (210) may obtain an image (952) based on the image (951) and the map information. The brightness levels of the object (902) of the image (952) may be set to be greater than the brightness levels of the object (901) of the image (951).

[0148] For example, the brightness levels of an object (903) in an image (953) may be set to be less than the brightness levels of an object (902) in an image (952). The processor (210) may reduce the second grayscale range based on identifying that a specified object (901) is included in the image (951). As the processor (210) reduces the second grayscale range, the processor (210) may reduce the rate of increase (or gain) of the brightness levels of an object (902) in an image (952) relative to the specified object (901) in the image (951). For example, the processor (210) may reduce the overall luminance increase rate of the image (952) to display the image (952) through the display (120).

[0149] FIG. 10A illustrates an example of operation of an electronic device for changing a grayscale range, according to one embodiment.

[0150] FIG. 10b illustrates an example of a change in an image according to a change in the tonal range, according to one embodiment.

[0151] FIG. 10c illustrates an example of an image change according to a change in the grayscale range, according to one embodiment.

[0152] Referring to FIG. 10A, in operation 1001, the processor (210) may obtain information regarding a single image. For example, the processor (210) may obtain information regarding a single image to determine a threshold grayscale level.

[0153] According to one embodiment, information about a single image may include information about a shooting mode of the single image (e.g., portrait shooting mode, food shooting mode, night scene shooting mode, or text shooting mode) and / or information about an object included in the single image. For example, the processor (210) may identify metadata of the single image. The processor (210) may identify a shooting mode of the single image based on the metadata of the single image. For example, the processor (210) may identify an object (or at least one object) included in the single image. The processor (210) may identify information about the object included in the single image. For example, the information about the object may include characteristics of the object, a shooting environment of the object, and / or a type of the object.

[0154] In operation 1002, the processor (210) may determine a threshold grayscale level. For example, the processor (210) may determine the threshold grayscale level based on information about a single image. The processor (210) may use the threshold grayscale level to distinguish a first region and a second region. For example, the processor (210) may identify a grayscale range exceeding the threshold grayscale level as a first grayscale range. The first region may have a grayscale range exceeding the threshold grayscale level (or a first grayscale range). The processor (210) may identify a grayscale range that is lower than or equal to the threshold grayscale level as a third grayscale range. The second region may have a grayscale range lower than or equal to the threshold grayscale level (or a third grayscale range).

[0155] For example, the processor (210) may determine a threshold grayscale level based on the shooting mode of the single image. If the shooting mode of the single image is a food shooting mode, the processor (210) may set the threshold grayscale level to a first threshold grayscale level. If the shooting mode of the single image is a night scene shooting mode, the processor (210) may set the threshold grayscale level to a second threshold grayscale level greater than the first threshold grayscale level. The processor (210) may determine the threshold grayscale level based on the shooting mode of the single image. The above-described first and second threshold grayscale levels are exemplary and are not limited thereto. According to an embodiment, if the shooting mode of the single image is a night scene shooting mode, the processor (210) may set the threshold grayscale level to a second threshold grayscale level less than or equal to the first threshold grayscale level.

[0156] For example, the processor (210) may determine a threshold grayscale level based on information about an object included in a single image. The processor (210) may identify that the single image includes food. Based on identifying that the single image includes food, the processor (210) may set the threshold grayscale level to a first threshold grayscale level. Based on identifying that the single image includes a building, the processor (210) may set the threshold grayscale level to a second threshold grayscale level greater than the first threshold grayscale level. The above-described first and second threshold grayscale levels are exemplary and are not limited thereto. According to an embodiment, the processor (210) may set the threshold grayscale level to a second threshold grayscale level less than or equal to the first threshold grayscale level based on identifying that the single image includes a building.

[0157] In operation 1003, the processor (210) may obtain map information for changing the grayscale range of the first region from the first grayscale range to the second grayscale range. For example, operation 1003 may correspond to operation 320 of FIG. 3.

[0158] For example, the processor (210) may determine a second tone range based on information about a single image. The processor (210) may obtain map information for changing the tone range of a first area from the first tone range to the second tone range based on information about a single image.

[0159] For example, based on the fact that the shooting mode of a single image is a food shooting mode, the processor (210) can identify a second tone range. For example, based on the fact that the shooting mode of a single image is a night scene shooting mode, the processor (210) can identify a second tone range. The second tone range identified in the night scene shooting mode can be distinguished from the second tone range identified in the food shooting mode.

[0160] In operation 1004, the processor (210) may store a file containing metadata including map information and a single image. For example, operation 1004 may correspond to operation 330 of FIG. 3.

[0161] Referring to FIG. 10b, the processor (210) can obtain a first image (1010). The processor (210) can obtain information about the first image (1010). For example, the processor (210) can identify the shooting mode of the first image (1010) based on metadata of the first image (1010). The processor (210) can identify that the shooting mode of the first image (1010) is a food shooting mode.

[0162] According to one embodiment, the processor (210) may identify a threshold grayscale level (1030) based on the shooting mode of the first image (1010). Based on the threshold grayscale level (1030), the processor (210) may identify an area corresponding to the object (1011) as a first area. The processor (210) may identify an area excluding the area corresponding to the object (1011) as a second area.

[0163] According to one embodiment, the processor (210) may identify a second grayscale range based on the shooting mode of the first image (1010). The processor (210) may obtain map information to visually emphasize the first region (i.e., the region corresponding to the object (1011)) relative to the second region. Using the map information, the processor (210) may change the grayscale range of the first region from the first grayscale range to a second grayscale range wider than the first grayscale range. The processor (210) may obtain a second image (1020) based on the first image (1010) and the map information. The brightness levels of the object (1021) of the second image (1020) may be set to be greater than the brightness levels of the object (1011) of the image (1010).

[0164] Graph (1031) represents normalized luminance levels according to normalized grayscale levels for the first image (1010). Graph (1032) represents normalized luminance levels according to normalized grayscale levels for the second image (1020).

[0165] For example, in the first image (1010), if the normalized grayscale level is '1', the normalized luminance level of the display (120) may be set to '1'. In the second image (1020), if the normalized grayscale level is '1', the normalized luminance level of the display (120) may be set to '1.2'. As the second image (1020) is displayed through the display (120) instead of the first image (1010), the luminance level may change from '1' to '1.2'. The ratio at which the luminance level changes may be referred to as the SDR-to-HDR ratio.

[0166] Referring to FIG. 10c, the processor (210) can obtain a first image (1060). The processor (210) can obtain information about the first image (1060). For example, the processor (210) can identify the shooting mode of the first image (1060) based on metadata of the first image (1060). The processor (210) can identify that the shooting mode of the first image (1060) is a night scene shooting mode.

[0167] According to one embodiment, the processor (210) may identify a threshold grayscale level (1080) based on the shooting mode of the first image (1060). Based on the threshold grayscale level (1080), the processor (210) may identify an area corresponding to the object (1061) as a first area. The processor (210) may identify an area excluding the area corresponding to the object (1061) as a second area. For example, the threshold grayscale level (1080) may be set lower than the threshold grayscale level (1030) of FIG. 10B.

[0168] According to one embodiment, the processor (210) may identify the second grayscale range based on the shooting mode of the first image (1060). For example, the second grayscale range identified based on the shooting mode of the first image (1060) may be distinguished from the second grayscale range identified based on the shooting mode of the first image (1010) of FIG. 10B.

[0169] For example, the processor (210) may obtain map information to visually emphasize a first region (i.e., a region corresponding to the object (1061)) relative to a second region. Using the map information, the processor (210) may change the grayscale range of the first region from a first grayscale range to a second grayscale range wider than the first grayscale range. The processor (210) may obtain a second image (1070) based on the first image (1060) and the map information. Brightness levels of the object (1071) of the second image (1070) may be set to be greater than brightness levels of the object (1061) of the image (1060).

[0170] Graph (1081) represents normalized luminance levels according to normalized grayscale levels for the first image (1060). Graph (1082) represents normalized luminance levels according to normalized grayscale levels for the second image (1070).

[0171] For example, in the first image (1060), if the normalized grayscale level is '1', the normalized luminance level of the display (120) may be set to '1'. In the second image (1070), if the normalized grayscale level is '1', the normalized luminance level of the display (120) may be set to '5'. As the second image (1070) is displayed through the display (120) instead of the first image (1060), the luminance level may change from '1' to '5'. The ratio at which the luminance level changes may be referred to as the SDR-to-HDR ratio.

[0172] Referring to FIGS. 10B and 10C, a rate at which a brightness level changes may be set based on a first image (e.g., a first image (1010), a first image (1060)). The processor (210) may set a rate at which the brightness level changes based on information about the first image (e.g., a shooting mode of the first image or information about an object included in the first image).

[0173] FIG. 11 is a block diagram of an electronic device (1101) within a network environment (1100) according to various embodiments. Referring to FIG. 11, in the network environment (1100), the electronic device (1101) may communicate with the electronic device (1102) via a first network (1198) (e.g., a short-range wireless communication network), or may communicate with at least one of the electronic device (1104) or the server (1108) via a second network (1199) (e.g., a long-range wireless communication network). In one embodiment, the electronic device (1101) may communicate with the electronic device (1104) via the server (1108). According to one embodiment, the electronic device (1101) may include a processor (1120), a memory (1130), an input module (1150), an audio output module (1155), a display module (1160), an audio module (1170), a sensor module (1176), an interface (1177), a connection terminal (1178), a haptic module (1179), a camera module (1180), a power management module (1188), a battery (1189), a communication module (1190), a subscriber identification module (1196), or an antenna module (1197). In some embodiments, the electronic device (1101) may omit at least one of these components (e.g., the connection terminal (1178)), or may have one or more other components added. In some embodiments, some of these components (e.g., sensor module (1176), camera module (1180), or antenna module (1197)) may be integrated into a single component (e.g., display module (1160)).

[0174] The processor (1120) may, for example, execute software (e.g., a program (1140)) to control at least one other component (e.g., a hardware or software component) of the electronic device (1101) connected to the processor (1120) and perform various data processing or operations. According to one embodiment, as at least a part of the data processing or operations, the processor (1120) may store commands or data received from other components (e.g., a sensor module (1176) or a communication module (1190)) in a volatile memory (1132), process the commands or data stored in the volatile memory (1132), and store result data in a non-volatile memory (1134). According to one embodiment, the processor (1120) may include a main processor (1121) (e.g., a central processing unit or an application processor) or an auxiliary processor (1123) (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor) that can operate independently or together with the main processor (1121). For example, when the electronic device (1101) includes the main processor (1121) and the auxiliary processor (1123), the auxiliary processor (1123) may be configured to use less power than the main processor (1121) or to be specialized for a given function. The auxiliary processor (1123) may be implemented separately from the main processor (1121) or as a part thereof.

[0175] The auxiliary processor (1123) may control at least a portion of functions or states associated with at least one component (e.g., a display module (1160), a sensor module (1176), or a communication module (1190)) of the electronic device (1101), for example, on behalf of the main processor (1121) while the main processor (1121) is in an inactive (e.g., sleep) state, or together with the main processor (1121) while the main processor (1121) is in an active (e.g., application execution) state. In one embodiment, the auxiliary processor (1123) (e.g., an image signal processor or a communication processor) may be implemented as a part of another functionally related component (e.g., a camera module (1180) or a communication module (1190)). In one embodiment, the auxiliary processor (1123) (e.g., a neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. The artificial intelligence models may be generated through machine learning. This learning can be performed, for example, on the electronic device (1101) itself where the artificial intelligence model is executed, or can be performed through a separate server (e.g., server (1108)). The learning algorithm can include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model can include multiple artificial neural network layers.The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to, or alternatively to, a hardware structure, an artificial intelligence model may include a software structure.

[0176] The memory (1130) can store various data used by at least one component (e.g., the processor (1120) or the sensor module (1176)) of the electronic device (1101). The data can include, for example, software (e.g., the program (1140)) and input data or output data for commands related thereto. The memory (1130) can include a volatile memory (1132) or a non-volatile memory (1134).

[0177] The program (1140) may be stored as software in memory (1130) and may include, for example, an operating system (1142), middleware (1144), or an application (1146).

[0178] The input module (1150) can receive commands or data to be used in a component of the electronic device (1101) (e.g., a processor (1120)) from an external source (e.g., a user) of the electronic device (1101). The input module (1150) can include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0179] The audio output module (1155) can output audio signals to the outside of the electronic device (1101). The audio output module (1155) can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. In one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0180] The display module (1160) can visually provide information to an external party (e.g., a user) of the electronic device (1101). The display module (1160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling the device. In one embodiment, the display module (1160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of a force generated by the touch.

[0181] The audio module (1170) can convert sound into an electrical signal, or vice versa, convert an electrical signal into sound. According to one embodiment, the audio module (1170) can acquire sound through the input module (1150), output sound through the sound output module (1155), or an external electronic device (e.g., electronic device (1102)) (e.g., speaker or headphone) directly or wirelessly connected to the electronic device (1101).

[0182] The sensor module (1176) can detect the operating status (e.g., power or temperature) of the electronic device (1101) or the external environmental status (e.g., user status) and generate an electrical signal or data value corresponding to the detected status. According to one embodiment, the sensor module (1176) can include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0183] The interface (1177) may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device (1101) with an external electronic device (e.g., the electronic device (1102)). In one embodiment, the interface (1177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0184] The connection terminal (1178) may include a connector through which the electronic device (1101) may be physically connected to an external electronic device (e.g., the electronic device (1102)). In one embodiment, the connection terminal (1178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0185] The haptic module (1179) can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that a user can perceive through tactile or kinesthetic sensations. In one embodiment, the haptic module (1179) may include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

[0186] The camera module (1180) can capture still images and videos. In one embodiment, the camera module (1180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0187] The power management module (1188) can manage the power supplied to the electronic device (1101). According to one embodiment, the power management module (1188) can be implemented as, for example, at least a part of a power management integrated circuit (PMIC).

[0188] A battery (1189) may power at least one component of the electronic device (1101). In one embodiment, the battery (1189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0189] The communication module (1190) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device (1101) and an external electronic device (e.g., electronic device (1102), electronic device (1104), or server (1108)), and the performance of communication through the established communication channel. The communication module (1190) may operate independently from the processor (1120) (e.g., application processor) and may include one or more communication processors that support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (1190) may include a wireless communication module (1192) (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (1194) (e.g., a local area network (LAN) communication module, or a power line communication module). Any of these communication modules may communicate with an external electronic device (1104) via a first network (1198) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (1199) (e.g., a long-range communication network such as a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (1192) may use subscriber information (e.g., an international mobile subscriber identity (IMSI)) stored in the subscriber identification module (1196) to verify or authenticate the electronic device (1101) within a communication network such as the first network (1198) or the second network (1199).

[0190] The wireless communication module (1192) can support 5G networks and next-generation communication technologies following the 4G network, such as NR access technology (new radio access technology). The NR access technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module (1192) can support, for example, a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate. The wireless communication module (1192) may support various technologies for securing performance in a high-frequency band, such as beamforming, massive multiple-input and multiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large scale antenna. The wireless communication module (1192) may support various requirements specified in the electronic device (1101), an external electronic device (e.g., the electronic device (1104)), or a network system (e.g., the second network (1199)). According to one embodiment, the wireless communication module (1192) may support a peak data rate (e.g., 20 Gbps or more) for eMBB implementation, a loss coverage (e.g., 164 dB or less) for mMTC implementation, or a U-plane latency (e.g., 0.5 ms or less for downlink (DL) and uplink (UL), or 1 ms or less for round trip) for URLLC implementation.

[0191] The antenna module (1197) can transmit or receive signals or power to or from an external device (e.g., an external electronic device). In one embodiment, the antenna module (1197) may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). In one embodiment, the antenna module (1197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as the first network (1198) or the second network (1199), may be selected from the plurality of antennas by, for example, the communication module (1190). A signal or power may be transmitted or received between the communication module (1190) and an external electronic device via the selected at least one antenna. In some embodiments, in addition to the radiator, another component (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module (1197).

[0192] According to various embodiments, the antenna module (1197) may form a mmWave antenna module. In one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent a first side (e.g., a bottom side) of the printed circuit board and capable of supporting a designated high frequency band (e.g., a mmWave band), and a plurality of antennas (e.g., an array antenna) disposed on or adjacent a second side (e.g., a top side or a side side) of the printed circuit board and capable of transmitting or receiving signals in the designated high frequency band.

[0193] At least some of the above components can be interconnected and exchange signals (e.g., commands or data) with each other via a communication method between peripheral devices (e.g., a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0194] According to one embodiment, commands or data may be transmitted or received between the electronic device (1101) and an external electronic device (1104) via a server (1108) connected to a second network (1199). Each of the external electronic devices (1102, or 704) may be the same or a different type of device as the electronic device (1101). According to one embodiment, all or part of the operations executed in the electronic device (1101) may be executed in one or more of the external electronic devices (1102, 1104, or 1108). For example, when the electronic device (1101) is to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device (1101) may, instead of or in addition to executing the function or service itself, request one or more external electronic devices to perform the function or at least a part of the service. One or more external electronic devices that receive the request may execute at least a portion of the requested function or service, or an additional function or service related to the request, and transmit the result of the execution to the electronic device (1101). The electronic device (1101) may process the result as is or additionally and provide it as at least a portion of a response to the request. For this purpose, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used, for example. The electronic device (1101) may provide an ultra-low latency service by using distributed computing or mobile edge computing, for example. In one embodiment, the external electronic device (1104) may include an Internet of Things (IoT) device. The server (1108) may be an intelligent server utilizing machine learning and / or a neural network.According to one embodiment, an external electronic device (1104) or server (1108) may be included within the second network (1199). The electronic device (1101) may be applied to intelligent services (e.g., smart homes, smart cities, smart cars, or healthcare) based on 5G communication technology and IoT-related technology.

[0195] FIG. 12 is a block diagram (1200) illustrating a camera module (1180) according to various embodiments. Referring to FIG. 12, the camera module (1180) may include a lens assembly (1210), a flash (1220), an image sensor (1230), an image stabilizer (1240), a memory (1250) (e.g., a buffer memory), or an image signal processor (1260). The lens assembly (1210) may collect light emitted from a subject that is a target of image capturing. The lens assembly (1210) may include one or more lenses. According to one embodiment, the camera module (1180) may include a plurality of lens assemblies (1210). In this case, the camera module (1180) may form, for example, a dual camera, a 360-degree camera, or a spherical camera. Some of the plurality of lens assemblies (1210) may have the same lens properties (e.g., angle of view, focal length, autofocus, f-number, or optical zoom), or at least one lens assembly may have one or more lens properties that are different from the lens properties of the other lens assemblies. A lens assembly (1210) may include, for example, a wide-angle lens or a telephoto lens.

[0196] The flash (1220) can emit light used to enhance light emitted or reflected from a subject. According to one embodiment, the flash (1220) can include one or more light-emitting diodes (e.g., red-green-blue (RGB) LED, white LED, infrared LED, or ultraviolet LED) or a xenon lamp. The image sensor (1230) can acquire an image corresponding to the subject by converting light emitted or reflected from the subject and transmitted through the lens assembly (1210) into an electrical signal. According to one embodiment, the image sensor (1230) can include one image sensor selected from among image sensors having different properties, such as an RGB sensor, a black and white (BW) sensor, an IR sensor, or a UV sensor, a plurality of image sensors having the same property, or a plurality of image sensors having different properties. Each image sensor included in the image sensor (1230) may be implemented using, for example, a CCD (charged coupled device) sensor or a CMOS (complementary metal oxide semiconductor) sensor.

[0197] The image stabilizer (1240) can move at least one lens or image sensor (1230) included in the lens assembly (1210) in a specific direction or control the operating characteristics of the image sensor (1230) (e.g., adjusting the read-out timing, etc.) in response to the movement of the camera module (1180) or the electronic device (1101) including the same. This allows compensating for at least some of the negative effects of the movement on the captured image. In one embodiment, the image stabilizer (1240) can detect such movement of the camera module (1180) or the electronic device (1101) by using a gyro sensor (not shown) or an acceleration sensor (not shown) disposed inside or outside the camera module (1180). According to one embodiment, the image stabilizer (1240) may be implemented as, for example, an optical image stabilizer. The memory (1250) may temporarily store at least a portion of the image acquired through the image sensor (1230) for the next image processing task. For example, when image acquisition is delayed due to a shutter or a plurality of images are acquired at high speed, the acquired original image (e.g., a Bayer-patterned image or a high-resolution image) may be stored in the memory (1250), and a corresponding copy image (e.g., a low-resolution image) may be previewed through the display module (1160). Thereafter, when a specified condition is satisfied (e.g., a user input or a system command), at least a portion of the original image stored in the memory (1250) may be acquired and processed by, for example, the image signal processor (1260). According to one embodiment, the memory (1250) may be configured as at least a portion of the memory (1130), or as a separate memory that operates independently therefrom.

[0198] The image signal processor (1260) can perform one or more image processing operations on an image acquired through an image sensor (1230) or an image stored in a memory (1250). The one or more image processing operations may include, for example, depth map generation, 3D modeling, panorama generation, feature extraction, image synthesis, or image compensation (e.g., noise reduction, resolution adjustment, brightness adjustment, blurring, sharpening, or softening). Additionally or alternatively, the image signal processor (1260) may perform control (e.g., exposure time control, read-out timing control, etc.) on at least one of the components included in the camera module (1180) (e.g., image sensor (1230)). The image processed by the image signal processor (1260) may be stored back in the memory (1250) for further processing or provided to an external component of the camera module (1180) (e.g., memory (1130), display module (1160), electronic device (1102), electronic device (1104), or server (1108). According to one embodiment, the image signal The processor (1260) may be configured as at least a part of the processor (1120), or may be configured as a separate processor that operates independently of the processor (1120). If the image signal processor (1260) is configured as a separate processor from the processor (1120), at least one image processed by the image signal processor (1260) may be displayed through the display module (1160) as is or after undergoing additional image processing by the processor (1120).

[0199] According to one embodiment, the electronic device (1101) may include a plurality of camera modules (1180), each having different properties or functions. In this case, for example, at least one of the plurality of camera modules (1180) may be a wide-angle camera, and at least another may be a telephoto camera. Similarly, at least one of the plurality of camera modules (1180) may be a front camera, and at least another may be a rear camera.

[0200] FIG. 13 is a block diagram (1300) of a display module (1160) according to various embodiments. Referring to FIG. 13, the display module (1160) may include a display (1310) and a display driver IC (DDI) (1330) for controlling the display (1310). The DDI (1330) may include an interface module (1331), a memory (1333) (e.g., a buffer memory), an image processing module (1335), or a mapping module (1337). The DDI (1330) may receive image information including, for example, image data or an image control signal corresponding to a command for controlling the image data, from another component of the electronic device (1101) through the interface module (1331). For example, according to one embodiment, image information may be received from a processor (1120) (e.g., a main processor (1121) (e.g., an application processor) or an auxiliary processor (1123) (e.g., a graphics processing unit) that operates independently of the function of the main processor (1121). The DDI (1330) may communicate with a touch circuit (1350) or a sensor module (1176) through the interface module (1331). In addition, the DDI (1330) may store at least a part of the received image information in the memory (1333), for example, in units of frames. The image processing module (1335) may, for example, perform preprocessing or postprocessing (e.g., resolution, brightness, or size adjustment) on at least a part of the image data based on at least a characteristic of the image data or a characteristic of the display (1310). The mapping module (1337) may output a voltage value or a value corresponding to the image data preprocessed or postprocessed through the image processing module (1335). Current values ​​can be generated.According to one embodiment, the generation of voltage values ​​or current values ​​may be performed at least in part based on, for example, properties of pixels of the display (1310) (e.g., arrangement of pixels (RGB stripe or pentile structure), or size of each sub-pixel). At least some pixels of the display (1310) may be driven at least in part based on, for example, the voltage values ​​or current values, so that visual information (e.g., text, images, or icons) corresponding to the image data may be displayed through the display (1310).

[0201] According to one embodiment, the display module (1160) may further include a touch circuit (1350). The touch circuit (1350) may include a touch sensor (1351) and a touch sensor IC (1353) for controlling the touch sensor (1351). The touch sensor IC (1353) may control the touch sensor (1351) to detect, for example, a touch input or a hovering input for a specific location of the display (1310). For example, the touch sensor IC (1353) may detect a touch input or a hovering input by measuring a change in a signal (e.g., voltage, light quantity, resistance, or charge quantity) for a specific location of the display (1310). The touch sensor IC (1353) may provide information (e.g., location, area, pressure, or time) regarding the detected touch input or hovering input to the processor (1120). According to one embodiment, at least a portion of the touch circuit (1350) (e.g., touch sensor IC (1353)) may be included as part of the display driver IC (1330), or as part of the display (1310), or as part of another component (e.g., auxiliary processor (1123)) disposed external to the display module (1160).

[0202] According to one embodiment, the display module (1160) may further include at least one sensor (e.g., a fingerprint sensor, an iris sensor, a pressure sensor, or an illuminance sensor) of the sensor module (1176), or a control circuit therefor. In this case, the at least one sensor or the control circuit therefor may be embedded in a part of the display module (1160) (e.g., the display (1310) or the DDI (1330)) or a part of the touch circuit (1350). For example, when the sensor module (1176) embedded in the display module (1160) includes a biometric sensor (e.g., a fingerprint sensor), the biometric sensor may obtain biometric information (e.g., a fingerprint image) associated with a touch input through a part of the display (1310). For another example, if the sensor module (1176) embedded in the display module (1160) includes a pressure sensor, the pressure sensor may obtain pressure information associated with a touch input through a portion or the entire area of ​​the display (1310). According to one embodiment, the touch sensor (1351) or the sensor module (1176) may be disposed between pixels of a pixel layer of the display (1310), or above or below the pixel layer.

[0203] Electronic devices according to the various embodiments disclosed in this document may take various forms. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. Electronic devices according to the embodiments of this document are not limited to the aforementioned devices.

[0204] The various embodiments of this document and the terminology used therein are not intended to limit the technical features described in this document to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the items, unless the context clearly indicates otherwise. In this document, each of the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" can include any one of the items listed together in the corresponding phrase among those phrases, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used merely to distinguish one component from another, and do not limit the components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as "coupled" or "connected" to another (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0205] The term "module" used in various embodiments of this document may include a unit implemented in hardware, and may be used interchangeably with terms such as logic, block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0206] Various embodiments of the present document may be implemented as software (e.g., a program (1140)) including one or more instructions stored in a storage medium (e.g., an internal memory (1136) or an external memory (1138)) readable by a machine (e.g., an electronic device (1101)). For example, a processor (e.g., a processor (1120)) of the machine (e.g., an electronic device (1101)) may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium.

[0207] According to one embodiment, the method according to various embodiments disclosed in the present document may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via an application store (e.g., Play Store™) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0208] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separately arranged in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added. The electronic device (1101) of FIG. 11 may be an example of the electronic device (101) of FIGS. 1 to 10C.

[0209] The technical problems to be achieved in the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by a person having ordinary knowledge in the technical field to which the present disclosure pertains.

[0210] According to one embodiment, an electronic device (e.g., electronic device (101) of FIGS. 1 to 10C or electronic device (1101) of FIG. 11) may include a display (e.g., display (120) or display module (1160) of FIG. 11), at least one processor including a processing circuit (e.g., processor (210) of FIGS. 1 to 10C or processor (1020) of FIG. 11), and a memory including one or more storage media storing instructions (e.g., memory (215) of FIGS. 1 to 10C or memory (1130) of FIG. 11). The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to acquire a single image (e.g., first image (130) of FIG. 4) based on a predetermined event. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to obtain, from the single image, map information (e.g., map information (140) of FIG. 4) for changing a gradation range of the first region of the single image from a first gradation range to a second gradation range wider than the first gradation range, for a first region of the single image that is visually emphasized relative to a second region of the single image when the single image is displayed. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to store, in the memory, metadata including the map information and a file including the single image.

[0211] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to determine at least one grayscale level based on configuration information regarding the single image. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to identify the first region and the second region within the single image based on the at least one grayscale level.

[0212] According to one embodiment, the setting information regarding the single image may include at least one of information regarding at least one camera for acquiring the single image, a shooting mode regarding the single image, or information regarding at least one object included in the single image.

[0213] In one embodiment, the at least one tone level may include a threshold tone level. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to identify a tone range exceeding the threshold tone level as the first tone range.

[0214] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to obtain a gain image (e.g., gain image (121) of FIG. 4) including the first region by removing the second region from the single image. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to obtain the map information based on the gain image.

[0215] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to remove distortion of at least one object included in the gain image using a designated algorithm. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to obtain the map information based on the gain image from which the distortion has been removed.

[0216] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to obtain a first processed image based on decreasing brightness levels of the gain image. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to obtain a second processed image based on performing correction on the first processed image. The instructions, when individually or collectively executed by the at least one processor, may cause the upper limb electronic device to remove distortion of the at least one object included in the gain image based on increasing brightness levels of the second processed image.

[0217] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to apply a specified filter to the gain image. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to obtain the map information based on the gain image to which the specified filter has been applied.

[0218] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to remove distortion of at least one object included in the gain image while maintaining an outline of the at least one object included in the gain image by applying the designated filter to the gain image.

[0219] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to identify that a specified object (e.g., the specified object (901) of FIG. 9B ) is included in the single image. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to reduce the second grayscale range based on identifying that the specified object is included in the single image.

[0220] According to one embodiment, the electronic device may include at least one camera. The predetermined event may include an event for acquiring multiple images using the at least one camera. The single image may be acquired based on the multiple images.

[0221] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to identify a brightness value of the display based on the metadata and the single image contained in the file. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to display another image configured based on the metadata and the single image using the display providing brightness according to the brightness value to display the single image.

[0222] According to one embodiment, a method performed in an electronic device (e.g., the electronic device (101) of FIGS. 1 to 10C or the electronic device (1101) of FIG. 11) including a display (e.g., the display (120) or the display module (1160) of FIG. 11) may include an operation of acquiring a single image (e.g., a first image (130) of FIG. 4) based on a predetermined event. The method may include an operation of acquiring, from the single image, map information (e.g., map information (140) of FIG. 4) for changing a gradation range of the first region from a first gradation range to a second gradation range wider than the first gradation range, for a first region of the single image visually emphasized with respect to a second region of the single image, when the single image is displayed. The method may include an operation of storing metadata including the map information and a file including the single image in a memory (e.g., memory (215) of FIGS. 1 to 10c or memory (1130) of FIG. 11).

[0223] According to one embodiment, the method may include an operation of determining at least one grayscale level based on setting information regarding the single image. The method may further include an operation of identifying the first region and the second region within the single image based on the at least one grayscale level.

[0224] According to one embodiment, the setting information regarding the single image may include at least one of information regarding at least one camera for acquiring the single image, a shooting mode regarding the single image, or information regarding at least one object included in the single image.

[0225] According to one embodiment, the at least one grayscale level may include a threshold grayscale level. The method may include an operation of identifying a grayscale range exceeding the threshold grayscale level as the first grayscale range.

[0226] In one embodiment, the method may include an operation of obtaining a gain image including the first region by removing the second region from the single image. The method may include an operation of obtaining the map information based on the gain image.

[0227] According to one embodiment, the method may include an operation of removing distortion of at least one object included in the gain image using a specified algorithm. The method may include an operation of obtaining the map information based on the gain image from which the distortion has been removed.

[0228] According to one embodiment, the method may include an operation of obtaining a first processed image based on decreasing brightness levels of the gain image. The method may include an operation of obtaining a second processed image based on performing a correction on the first processed image. The method may include an operation of removing distortion of the at least one object included in the gain image based on increasing brightness levels of the second processed image.

[0229] According to one embodiment, the method may include an operation of applying a specified filter to the gain image. The method may include an operation of obtaining the map information based on the gain image to which the specified filter has been applied.

[0230] According to one embodiment, the method may include removing distortion of at least one object included in the gain image while maintaining an outline of the at least one object included in the gain image by applying the specified filter to the gain image.

[0231] In one embodiment, the method may include an operation of identifying that a specified object is included within the single image. The method may include an operation of reducing the second grayscale range based on identifying that the specified object is included within the single image.

[0232] According to one embodiment, the electronic device may include at least one camera. The predetermined event may include an event for acquiring multiple images using the at least one camera. The single image may be acquired based on the multiple images.

[0233] In one embodiment, the method may include an operation of identifying a brightness value of the display based on the metadata and the single image included in the file. The method may include an operation of displaying another image configured based on the metadata and the single image using the display that provides brightness according to the brightness value to display the single image.

[0234] According to one embodiment, a non-transitory computer-readable storage medium may store one or more programs. The one or more programs may include instructions that, when executed by a processor of an electronic device, cause the electronic device to acquire a single image based on a predetermined event. The one or more programs may include instructions that, when executed by the processor of the electronic device, cause the electronic device to acquire map information from the single image for changing a gradation range of the first region of the single image from a first gradation range to a second gradation range wider than the first gradation range, for a first region of the single image that is visually emphasized relative to a second region of the single image, when the single image is displayed. The one or more programs may include instructions that, when executed by the processor of the electronic device, cause the electronic device to store, in the memory, metadata including the map information and a file including the single image.

[0235] According to the above-described embodiment, an electronic device can generate a gain map from a single exposure image. The electronic device can enhance the brightness of a display based on the gain map (or map information). By enhancing the brightness of the display based on the gain map, the electronic device can provide an HDR experience. Accordingly, the electronic device can obtain a gain map from an existing legacy SDR image and generate an image having an HDR effect using the obtained gain map. The electronic device can display the image having the HDR effect through the display.

[0236] The effects that can be obtained from the present disclosure are not limited to the effects mentioned above, and other effects that are not mentioned will be clearly understood by a person having ordinary skill in the art to which the present disclosure pertains.

[0237] As used herein, the term "if" will be understood to mean "when, upon," "in response to determining," or "in response to detecting," depending on the context. Similarly, "if it is determined to," or "if [the stated condition or event] is detected," will optionally be understood to mean "upon determining," or "in response to determining," "upon detecting [the stated condition or event]," or "in response to detecting [the stated condition or event]."

[0238] The devices described above may be implemented as hardware components, software components, and / or a combination of hardware components and software components. For example, the devices and components described in the embodiments may be implemented using one or more general-purpose computers or special-purpose computers, such as a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing instructions and responding to them. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing device is sometimes described as being used alone; however, one of ordinary skill in the art will recognize that the processing device may include multiple processing elements and / or multiple types of processing elements. For example, a processing unit may include multiple processors, or a processor and a controller. Other processing configurations, such as parallel processors, are also possible.

[0239] Software may include a computer program, code, instructions, or a combination of one or more of these, which may configure a processing device to perform a desired operation or may independently or collectively command the processing device. The software and / or data may be embodied in any type of machine, component, physical device, computer storage medium, or device for interpretation by the processing device or for providing instructions or data to the processing device. The software may also be distributed over networked computer systems and stored or executed in a distributed manner. The software and data may be stored on one or more computer-readable recording media.

[0240] The method according to the embodiment may be implemented in the form of program commands that can be executed through various computer means and recorded on a computer-readable medium. In this case, the medium may be one that continuously stores a computer-executable program or one that temporarily stores it for execution or download. In addition, the medium may be various recording means or storage means in the form of a single or multiple hardware combinations, and is not limited to a medium directly connected to a computer system, but may also be distributed over a network. Examples of the medium may include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and those configured to store program commands, including ROM, RAM, and flash memory. In addition, examples of other media may include recording media or storage media managed by app stores that distribute applications, sites that supply or distribute various software, servers, etc.

[0241] Although the embodiments described above have been described by way of limited examples and drawings, those skilled in the art will appreciate that various modifications and variations can be made based on the above teachings. For example, appropriate results can still be achieved even if the described techniques are performed in a different order than described, and / or components of the described systems, structures, devices, circuits, etc. are combined or combined in a different manner than described, or are replaced or substituted with other components or equivalents.

[0242] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims described below.

Claims

1. In electronic devices, display; At least one processor comprising a processing circuit; and A memory comprising one or more storage media storing instructions, The above instructions, when individually or collectively executed by the at least one processor, Based on a predetermined event, a single image is acquired, For a first region of the single image that is visually emphasized with respect to a second region of the single image, when the single image is displayed, map information for changing the gradation range of the first region from a first gradation range to a second gradation range wider than the first gradation range is obtained from the single image, Causing the electronic device to store metadata including said map information and a file including said single image in the memory; Electronic devices.

2. In the first paragraph, when the instructions are individually or collectively executed by the at least one processor, Based on the setting information about the single image, at least one tone level is determined, Further causing the electronic device to identify the first region and the second region within the single image based on the at least one tone level; Electronic devices.

3. In the second paragraph, the setting information regarding the single image is, At least one of information about at least one camera for acquiring the single image, a shooting mode for the single image, or information about at least one object included in the single image, Electronic devices.

4. In the second paragraph, at least one tone level is, Including critical tone levels, The above instructions, when individually or collectively executed by the at least one processor, Further causing the electronic device to identify a tone range exceeding the threshold tone level as the first tone range. Electronic devices.

5. In the first paragraph, when the instructions are individually or collectively executed by the at least one processor, By removing the second region from the single image, a gain image including the first region is obtained, Further causing the electronic device to obtain the map information based on the above gain image, Electronic devices.

6. In the fifth paragraph, when the instructions are individually or collectively executed by the at least one processor, Using a specified algorithm, distortion of at least one object included in the gain image is removed, Further causing the electronic device to obtain the map information based on the gain image from which the distortion has been removed. Electronic devices.

7. In the sixth paragraph, when the instructions are individually or collectively executed by the at least one processor, Based on reducing the brightness levels of the above gain image, a first processed image is obtained, Based on performing correction on the first processed image, a second processed image is obtained, Further causing the upper limb electronic device to remove the distortion of the at least one object included in the gain image based on increasing the brightness levels of the second processed image. Electronic devices.

8. In the fifth paragraph, the instructions, when individually or collectively executed by the at least one processor, Apply the specified filter to the above gain image, Further causing the electronic device to obtain the map information based on the gain image to which the above-mentioned specified filter is applied. Electronic devices.

9. In the 8th paragraph, when the instructions are individually or collectively executed by the at least one processor, Further causing the electronic device to remove distortion of at least one object included in the gain image while maintaining an outline of the at least one object included in the gain image by applying the specified filter to the gain image. Electronic devices.

10. In the first paragraph, when the instructions are individually or collectively executed by the at least one processor, Identifying that a specified object is contained within the single image above, Further causing the electronic device to reduce the second tone range based on identifying that the specified object is included within the single image. Electronic devices.

11. In the first paragraph, the electronic device, Contains at least one camera, The above predetermined event is, comprising an event for acquiring a plurality of images using at least one camera; The above single image is, Based on the above multiple images, obtained, Electronic devices.

12. In the first paragraph, the instructions, when individually or collectively executed by the at least one processor, Identifying the brightness value of the display based on the metadata and the single image contained in the above file, Further causing the electronic device to display another image configured based on the metadata and the single image by using the display providing brightness according to the brightness value to display the single image. Electronic devices.

13. A method performed in an electronic device including a display, An action to acquire a single image based on a predetermined event; For a first region of the single image that is visually emphasized with respect to a second region of the single image, when the single image is displayed, an operation of acquiring map information for changing the gradation range of the first region from a first gradation range to a second gradation range wider than the first gradation range, from the single image; and Comprising an operation of storing a file including metadata including said map information and said single image in said memory. method.

14. In the 13th paragraph, the method, An operation of determining at least one tone level based on setting information regarding the single image; and Further comprising an operation of identifying the first region and the second region within the single image based on the at least one tonal level. method.

15. In a non-transitory computer-readable storage medium storing one or more programs, said one or more programs, when executed by a processor of an electronic device having a display, Based on a predetermined event, a single image is acquired, For a first region of the single image that is visually emphasized with respect to a second region of the single image, when the single image is displayed, map information for changing the gradation range of the first region from a first gradation range to a second gradation range wider than the first gradation range is obtained from the single image, instructions causing the electronic device to store in the memory a file comprising metadata including said map information and said single image; A non-transitory computer-readable storage medium.

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