Program and Information Processing Device

Abstract

To allow quality of an image that a user likes to be reflected on an imaging device (a camera).SOLUTION: A program causes a computer to function as an analysis target image quality adjusting unit for generating an analysis target image. The analysis target image quality adjusting unit generates an adjusted analysis target image which is used with an analysis target RAW image to determine an image quality setting parameter of a taken image acquired by an imaging device. In this case, the adjusted analysis target image is generated by performing image quality adjusting processing on an analysis target RAW image different from the analysis target RAW image, on the basis of image quality adjusting information showing an image quality adjusting value of the image quality adjustment processing on the adjustment target RAM image.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] This technology relates to programs and information processing devices Place Specifically, it relates to programs that can satisfactorily reflect the user's preferred image quality on an imaging device.

Background Art

[0002] When a user takes a photo with a digital camera or smartphone, the output forms of the obtained images are roughly classified into two major types: JPG (Joint Photographic Experts Group) and RAW. JPG is a form after the camera's signal processing and is a general-purpose format that most image viewing applications on a PC (personal computer) support.

[0003] RAW is a format premised on subsequent processing and editing. The user can freely adjust the adjustment items of the RAW development application as they like, and has the feature that they can finish it to the preferred image quality. Photos processed from RAW data are widely circulated in the world, and users who view them have an increasing opportunity to touch many photos with preferred image quality.

[0004] It can be said that JPG has high immediacy but low extensibility, while RAW has low immediacy and is time-consuming but high extensibility. If an imaging image with the same image quality as when processing RAW data can be immediately obtained, it can reduce the user's effort, and at the same time, there is an advantage that the user can always obtain an imaging image with the preferred image quality at the time of shooting.

[0005] For example, Patent Document 1 describes presenting a plurality of images obtained by executing image editing processing using a plurality of preset processing contents for thumbnail image data as additional information of image data, making it possible for the user to predict the processing content of the image data, and enabling the user to easily obtain a preferred image.

Prior Art Documents

[0006] [Patent Document 1] Japanese Patent Publication No. 2014-068228 [Overview of the Initiative] [Problems that the invention aims to solve]

[0007] The purpose of this technology is to enable users to accurately reflect their preferred image quality in the imaging device (camera). [Means for solving the problem]

[0008] The concept behind this technology is: The computer functions as an analysis target image quality adjustment unit, which generates an adjusted analysis target image used together with the analysis target RAW image for determining the image quality setting parameters of the captured image acquired by the imaging device, by performing image quality adjustment processing on an analysis target RAW image different from the adjustment target RAW image based on image quality adjustment information indicating the image quality adjustment values ​​for the image quality adjustment processing on the adjustment target RAW image. It's in the program.

[0009] This technology is a program that makes a computer function as an image quality adjustment unit for generating images to be analyzed. The image quality adjustment unit generates an adjusted image to be analyzed, which is used together with the raw image to be analyzed to determine the image quality setting parameters of the captured image acquired by the imaging device. In this case, the adjusted image to be analyzed is generated by performing image quality adjustment on an image to be analyzed that is different from the raw image to be adjusted, based on image quality adjustment information that indicates the image quality adjustment values ​​for the image quality adjustment process on the raw image to be adjusted.

[0010] In this technology, image quality adjustment processing is performed on the RAW image to be analyzed based on image quality adjustment information indicating the image quality adjustment values ​​for the RAW image to be adjusted. This generates an adjusted image to be analyzed that is used together with the RAW image to be analyzed to determine the image quality setting parameters of the captured image acquired by the imaging device. In this case, the image quality setting parameters of the captured image can be determined using the RAW image to be analyzed and the adjusted image to be analyzed, allowing the user's preferred image quality to be reflected in the imaging device with greater accuracy.

[0011] Furthermore, in this technology, for example, the image quality adjustment information may include information indicating at least one adjustment value from among color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment. This allows the imaging device to reflect the user's preferred image quality corresponding to at least one of the color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment.

[0012] Furthermore, in this technology, for example, the image quality adjustment unit for the analysis target may generate an adjusted image for analysis by performing the same image quality adjustment process on the analysis target RAW image as the image quality adjustment process performed on the adjustment target RAW image. This allows the imaging device to reflect the same image quality adjustment process that the user has applied to an image with their preferred image quality.

[0013] Furthermore, in this technology, for example, the image quality adjustment information may be information indicating the adjustment values ​​of multiple image quality adjustment items, and the analysis target image quality adjustment unit may generate an adjusted analysis target image based on selected image quality adjustment information indicating the adjustment values ​​of the image quality adjustment items selected by the user from among the multiple image quality adjustment items. This allows the image quality corresponding to the image quality adjustment items selected by the user to be reflected in the imaging device.

[0014] Furthermore, in this technology, for example, the RAW image to be analyzed may be provided by an external device different from the device equipped with a computer. In this case, the external device can modify or change the RAW image to be analyzed as appropriate, and the memory capacity of the device equipped with a computer can be kept low.

[0015] Furthermore, in this technology, for example, the image quality adjustment information may be information indicating the adjustment values ​​of multiple image quality adjustment items, and the RAW image to be analyzed may have multiple image regions, with each of the multiple image regions corresponding to at least one of the multiple image quality adjustment items. This makes it possible to accurately calculate (determine) the image quality setting parameters for matching multiple image quality adjustment items using a single RAW image to be analyzed.

[0016] Furthermore, in this technology, for example, the image quality adjustment unit for the image to be analyzed may generate an adjusted image to be analyzed based on image quality adjustment information in response to an operation by the user to reflect image quality settings. In this case, the image quality adjustment information reflected in the RAW image to be analyzed may indicate the image quality adjustment values ​​when the user performs image quality adjustment processing to achieve their preferred image quality on the RAW image to be adjusted.

[0017] Furthermore, in this technology, for example, the image quality adjustment unit for analysis may associate the adjusted image for analysis with image type information indicating the type of image content of the RAW image to be adjusted. This allows different image quality adjustment processes to be applied to the imaging device for each type of image content of the RAW image to be adjusted.

[0018] Furthermore, in this technology, for example, the image quality setting parameters may be determined for each image type information indicating the type of image content of the RAW image to be adjusted. This allows different image quality adjustment processing to be applied to the imaging device for each type of image content of the RAW image to be adjusted. In this case, for example, the image type information may include information indicating the type of subject. This allows different image quality adjustment processing to be applied to the imaging device for each type of subject.

[0019] Furthermore, in this technology, for example, the image quality adjustment unit for analysis may select a target RAW image from a plurality of candidate RAW images for analysis, based on shooting condition information indicating the shooting conditions of the target RAW image. In this case, by selecting a target RAW image that is suitable for the shooting conditions of the target RAW image, the user's preferred image quality can be reflected in the imaging device with greater accuracy.

[0020] Furthermore, in this technology, the computer may be configured to function as a quality setting parameter determination unit that determines quality setting parameters based on the RAW image to be analyzed and the adjusted image to be analyzed. This allows the program to determine the quality setting parameters.

[0021] Furthermore, in this technology, for example, the image quality setting parameter determination unit may determine the image quality setting parameters such that the difference between a first image quality evaluation value, which indicates the evaluation of the image quality of the adjusted image generated by performing image quality adjustment processing on the RAW image to be analyzed based on the image quality setting parameters, and a second image quality evaluation value, which indicates the evaluation of the image quality of the adjusted image to be analyzed, is less than or equal to a predetermined value. In this case, manually adjusting the image quality setting parameters would require a great deal of effort, whereas by using this system, the image quality setting parameters can be calculated (determined) well without manual intervention.

[0022] Furthermore, in this technology, for example, the first image quality evaluation value and the second image quality evaluation value may be evaluation values ​​that evaluate at least one of the following: color reproduction, contrast, resolution, and noise level. This makes it possible to determine the image quality setting parameters to match at least one of the image quality aspects of color reproduction, contrast, resolution, and noise level.

[0023] Also, in the present technology, for example, the computer may be made to function as an adjustment target image quality adjustment unit that executes an image quality adjustment process on an adjustment target RAW image based on image quality adjustment information. As a result, the image quality adjustment process of the adjustment target RAW image can be performed by this program.

[0024] Also, in the present technology, for example, the image quality adjustment value may be determined by a user's image quality adjustment operation on the adjustment target RAW image. As a result, the user's image quality adjustment operation can be reflected in the image quality adjustment process for the analysis target RAW image.

[0025] Also, another concept of the present technology is By performing an image quality adjustment process on an analysis target RAW image different from the adjustment target RAW image based on image quality adjustment information indicating an image quality adjustment value of the image quality adjustment process for the adjustment target RAW image, an adjusted analysis target image used together with the analysis target RAW image for determining image quality setting parameters of a captured image acquired by an imaging device is generated, and an analysis target image quality adjustment unit is provided. in an information processing apparatus.

[0026] Also, still another concept of the present technology is having an information processing apparatus and a server, wherein the information processing apparatus By performing an image quality adjustment process on an analysis target RAW image different from the adjustment target RAW image based on image quality adjustment information indicating an image quality adjustment value of the image quality adjustment process for the adjustment target RAW image, an adjusted analysis target image used together with the analysis target RAW image for determining image quality setting parameters of a captured image acquired by an imaging device is generated, and an analysis target image quality adjustment unit is provided. wherein the server is provided with an image quality setting parameter determination unit that determines the image quality setting parameters based on the analysis target RAW image and the adjusted analysis target image generated by the analysis target image quality adjustment unit. in an information processing system. [[ID=二十九]]

Brief Description of the Drawings

[0027] [Figure 1] This is a block diagram showing an example configuration of an information processing system as an embodiment. [Figure 2] This is a diagram illustrating the processing of PC applications 1 and 2. [Figure 3] This is a block diagram showing an example of a camera configuration. [Figure 4] This is a block diagram showing an example of a PC (cloud server) configuration. [Figure 5] This diagram shows an example of a functional block diagram for a PC and a cloud server. [Figure 6] This figure shows an example of the PC UI display related to the user's image quality adjustment operations. [Figure 7] This figure shows an example of the PC UI display related to the user's image quality adjustment operations. [Figure 8] This figure shows an example of the PC UI display related to the user's image quality adjustment operations. [Figure 9] This figure shows an example of the PC UI display related to the user's image quality adjustment operations. [Figure 10] This figure shows an example of the PC UI display related to the user's image quality adjustment operations. [Figure 11] This figure shows an example of the PC UI display related to the user's image quality adjustment operations. [Figure 12] This diagram illustrates how image quality setting parameters are imported into the camera. [Figure 13] This figure shows an example of the PC UI display related to the user's image quality adjustment operations. [Figure 14] This diagram shows another example of a functional block diagram for a PC and a cloud server. [Figure 15] This diagram illustrates an example of retaining multiple image quality setting parameters. [Figure 16] This diagram illustrates another example of maintaining multiple image quality setting parameters. [Figure 17] This diagram illustrates how a user can manually associate the RAW image to be adjusted with the type of subject. [Figure 18] This flowchart provides a schematic example of the process when a user manually associates the RAW image to be adjusted with the type of subject (person). [Figure 19] This diagram illustrates how to automatically associate the RAW image to be adjusted with the type of subject. [Figure 20] This flowchart provides a schematic example of the process used when automatically mapping the RAW image to be adjusted to the type of subject (person). [Figure 21] This diagram illustrates how a camera can have image quality setting parameters that support many different types of image content. [Figure 22] This flowchart provides a schematic example of the processing involved when using a camera equipped with image quality setting parameters that support a wide variety of image content types. [Figure 23] This diagram shows another example of a functional block diagram for a PC and a cloud server. [Figure 24] This diagram shows another example of a functional block diagram for a PC and a cloud server. [Modes for carrying out the invention]

[0028] The following describes embodiments for carrying out the invention. The description will be given in the following order. 1. Embodiment 2. Variations

[0029] <1. Embodiment> [Information Processing Systems] Figure 1 shows an example configuration of an information processing system 10 as an embodiment. This information processing system 10 includes a camera 100, a PC 200, and a cloud server 300. The camera 100 and the PC 200 are connected by a predetermined digital interface, such as a USB cable. The PC 200 is connected to the cloud server 300 via a network 400 such as the Internet. The camera 100 is also capable of connecting to the cloud server 300 via the network 400.

[0030] Camera 100 processes the RAW image of the subject to generate a JPG file, records it to a recording medium, or transmits it to an external device as needed. Camera 100 also generates a RAW image file based on the RAW image of the subject, records it to a recording medium, or transmits it to an external device as needed. While this description assumes the generation of a JPG file, other file types, such as BMP files, may also be used. The following explanation assumes the generation of a JPG file.

[0031] The PC200 has two applications: Application 1 and Application 2. Application 1, as schematically shown in Figure 2(a), processes the RAW image (RAW image to be adjusted) related to the subject's photography to generate a JPG file as the output image. Although it is stated here that a JPG file is generated, other file types, such as BMP files, may also be used. The following explanation assumes that a JPG file is generated.

[0032] In this case, image quality adjustments are made based on the user's image quality adjustment operations, and the image is developed to achieve the user's preferred image quality. The user can perform operations such as color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment.

[0033] Here, we will explain the development process in Application 1 and the development process within Camera 100. Signal processing in application 1 and camera 100 generally differ in terms of accuracy, processing order, and algorithms. Even if the processing itself differs, the key feature of this technology is to ensure that the image captured by camera 100 is as close as possible to the image the user prefers to achieve in application 1.

[0034] In this case, the PC200's display shows the output image along with the RAW image being adjusted, allowing the user to check whether the output image quality is to their liking. For example, when the output image quality is to their liking as a result of the quality adjustment operation, the user can press the "Apply to Camera" button displayed on the PC200's display to transition to the processing of Application 2, and further to the calculation of the image quality setting parameters for the captured image acquired by Camera 100.

[0035] The user's action of pressing the "Apply to Camera" button, as described above, corresponds to the user's action of applying image quality settings. In response to this action, Application 1 notifies Application 2 of the image quality adjustment information. Application 2 then performs development processing on the RAW image to be analyzed to generate an adjusted image to be analyzed. This allows the image quality adjustment information applied to the RAW image to be to indicate the image quality adjustment values ​​when the user performs image quality adjustment processing on the RAW image to be adjusted to their preferred image quality.

[0036] In this case, the image quality adjustment value is determined by the user's image quality adjustment operations on the target RAW image, as described above, and the user's image quality adjustment operations can be reflected in the image quality adjustment processing of the target RAW image.

[0037] Application 2, as schematically shown in Figure 2(b), processes a RAW image suitable for analysis (the RAW image to be analyzed) to generate a JPG file as the output image. The processing in this case is the same as the processing in Application 1, and the image quality adjustment is performed based on the image quality adjustment information that indicates the image quality adjustment values ​​of the image quality adjustment processing in Application 1. As a result, the output image in Application 2 becomes the adjusted image to be analyzed.

[0038] In this case, the adjusted image to be analyzed may be generated by applying the same image quality adjustment process to the RAW image to be analyzed as the image quality adjustment process applied to the RAW image to be adjusted. This allows the camera 100 to reflect the same image quality adjustment process that the user has applied to an image with their preferred image quality.

[0039] As described above, in relation to the development process in Application 1, the user performs operations such as color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment. The image quality adjustment process in the development process of Application 2 is performed based on image quality adjustment information that indicates the image quality adjustment values ​​of the image quality adjustment process in Application 1, as described above. This image quality adjustment information may include information indicating at least one adjustment value for color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment. This allows the camera 100 to reflect the user's preferred image quality corresponding to at least one of the color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment.

[0040] Here, we will explain the RAW image being analyzed. This RAW image is created to accurately calculate image quality setting parameters (parameter sets) such as color reproduction, contrast, resolution, and noise level. A key feature of this RAW image is that it can reflect the processing content more accurately than predicting the content from a processed general image.

[0041] There are no restrictions on the RAW images themselves that are analyzed; for example, they can be created to calculate finer color differences, or to calculate finer contrast differences, or their form can be determined according to the purpose.

[0042] The image quality adjustment information, which indicates the image quality adjustment values ​​for the image quality adjustment process in Application 1 described above, is information that indicates the adjustment values ​​for multiple image quality adjustment items. Here, image quality adjustment items include, for example, color reproduction, contrast, resolution, and noise level. The RAW image to be analyzed is assumed to have multiple image regions, with each of the multiple image regions corresponding to at least one of the multiple image quality adjustment items. This makes it possible to accurately calculate the image quality setting parameters for matching multiple image quality adjustment items in a single RAW image to be analyzed.

[0043] The RAW image to be analyzed may include an image area (chart) with a series of color patches, such as a Macbeth chart, which is commonly used, to evaluate color reproduction, contrast, and noise, as shown in Figure 2(b). Alternatively, the RAW image to be analyzed may include image areas for evaluating color reproduction, contrast, and noise separately, instead of this Macbeth chart.

[0044] There is no need to define a single RAW image to be analyzed; the image used can be changed as appropriate depending on the item being evaluated. For example, if you want to accurately evaluate color reproduction, you can use an image containing the image area of ​​the color patch, and if you want to evaluate both color reproduction and resolution, you can use an image containing the image area that allows for accurate evaluation of both.

[0045] The PC200 can use RAW images stored in its own memory (storage unit) as the RAW images to be analyzed, but they may also be provided by an external device, such as a cloud server 300. By providing the images by an external device in this way, the RAW images to be analyzed can be modified or changed as needed, and the memory capacity of the PC200 can be kept low.

[0046] Returning to Figure 1, the cloud server 300 uses the RAW image to be analyzed and the adjusted image to be analyzed generated by application 2 on PC 200 to determine the image quality setting parameters for the captured image acquired by camera 100.

[0047] In this case, the image quality setting parameters are determined such that the difference between a first image quality evaluation value, which indicates the evaluation of the image quality of the adjusted image generated by performing image quality adjustment processing on the RAW image to be analyzed based on the image quality setting parameters, and a second image quality evaluation value, which indicates the evaluation of the image quality of the adjusted image to be analyzed, is less than or equal to a predetermined value. For example, the first and second image quality evaluation values ​​are evaluation values ​​that evaluate at least one of the following: color reproduction, contrast, resolution, and noise level.

[0048] The image quality setting parameters determined by the cloud server 300 are supplied to the camera 100 via the PC 200 or directly from the cloud server 300 and used. This makes it possible for the camera 100 to obtain an image with the same image quality as the output image obtained by image quality adjustment processing based on the user's image quality adjustment operations in application 1 on the PC 200.

[0049] "Example camera configuration" Figure 3 shows an example configuration of camera 100. Camera 100 includes a control unit 101, a memory 102, an operation unit 103, a display unit 104, a recording / playback unit 105, and a communication unit 106. Camera 100 also includes an optical system 111, an imager 112, a RAW data processing unit 113, a RAW development unit 114, a JPG generation unit 115, and a RAW generation unit 116. Note that the configuration shown here is just one example, and some of the components may be omitted. Furthermore, it may include components other than those shown here.

[0050] The control unit 101 is equipped with a CPU (Central Processing Unit) and controls the entire camera 100. The memory 102 stores the CPU's control program. This memory 102 also constitutes the CPU's workspace and stores intermediate and final results of processing performed by the CPU. Furthermore, this memory 102 stores image quality setting parameters generated by the cloud server 300 and received by the communication unit 106, which will be described later.

[0051] The operation unit 103 consists of operation buttons, a touch panel, etc., and is the part that allows the user to perform various operations on the camera 100. The display unit 104 consists of an LCD panel, an organic EL panel, etc., and displays captured images as well as menu screens, settings screens, etc. The operation unit 103 and the display unit 104 constitute the user interface.

[0052] The recording / playback unit 105 records the generated JPG files and RAW image files, as described later, onto a recording medium and plays them back as needed. In this case, the recording medium may be a removable recording medium such as a memory card. The communication unit 106 communicates with external devices via wired or wireless connection. In this embodiment, it communicates with the PC 200 or with the cloud server 300 via the network 400.

[0053] The optical system 111 includes lenses such as a cover lens, zoom lens, and focus lens, as well as an aperture mechanism. This optical system 111 guides light (incident light) from the subject and focuses it on the imager 112. The imager 112 is, for example, a CMOS (Complementary Metal Oxide Semiconductor) type or a CCD (Charge Coupled Device) type imager. The imager 112 outputs the imaging signal as digital data to the subsequent RAW data processing unit 113.

[0054] The RAW data processing unit 113 performs processing on the RAW data output from the imager 112, such as pixel defect correction, color mixing correction, and flicker correction. The RAW development unit 114 develops the RAW data processed by the RAW data processing unit 113 to obtain YC data.

[0055] The RAW development unit 114 includes a brightness adjustment unit 121, a simultaneous processing unit 122, a white balance adjustment unit 125, a sharpness / noise adjustment unit 124, a color / contrast adjustment unit 125, and a YC generation unit 126.

[0056] The brightness adjustment unit 121 adjusts the brightness of the RAW data according to the set parameters. The simultaneous processing unit 122 performs color separation on the RAW data output from the brightness adjustment unit 121 so that the image data for each pixel has all the color components of R (red), G (green), and B (blue). For example, in the case of an imager 112 using a Bayer array color filter, demosaicing is performed as the color separation process.

[0057] The white balance adjustment unit 123 adjusts the white balance of the R, G, and B image data (three primary color data) output from the simultaneous processing unit 122 according to the set parameters. The sharpness / noise adjustment unit 124 adjusts the sharpness and noise of the R, G, and B image data output from the white balance adjustment unit 123 according to the set parameters.

[0058] The color / contrast adjustment unit 125 adjusts the color and contrast of the R, G, B image data output from the sharpness / noise adjustment unit 124 according to the set parameters. The YC generation unit 126 performs color gradation reproduction processing and gamma processing on the R, G, B image data output from the color / contrast adjustment unit 125, and then converts this R, G, B image data into a YC signal (luminance signal (Y) and chrominance signal (Cb, Cr)) according to a predetermined calculation formula.

[0059] The JPG generation unit 115 generates a JPG file based on the YC signal output from the RAW development unit 114 (YC generation unit 126). The generated JPG file is recorded on a recording medium by the recording / playback unit 105, played back as needed, used for image display, or transmitted to an external device via the communication unit 106.

[0060] Furthermore, the user can adjust the parameters in each adjustment section of the RAW development unit 114 by operating the control unit 103. In addition, the user can set image quality setting parameters determined by the cloud server 300 based on the user's operations as parameters in each adjustment section of the RAW development unit 114. In this case, the camera 100 can obtain an image capture image (JPG image) with the same image quality as the output image obtained by image quality adjustment processing based on the user's image quality adjustment operations in application 1 on the PC 200.

[0061] The RAW generation unit 116 generates a RAW data file based on the RAW data processed by the RAW data processing unit 113. The RAW data contained in this RAW data file may be either uncompressed RAW data or compressed RAW data. The RAW data file thus generated is recorded on a recording medium by the recording / playback unit 105, played back as needed, and transmitted to an external device via the communication unit 106.

[0062] "Example PC configurations" Figure 4 shows an example configuration of PC200. PC200 includes a CPU 201, ROM 202, RAM 203, bus 204, input / output interface 205, operation unit 206, display unit 207, storage unit 208, drive 209, connection port 210, and communication unit 211. Note that the configuration shown here is just one example, and some of the components may be omitted. Furthermore, it may include components other than those shown here.

[0063] The CPU 201 functions, for example, as an arithmetic processing unit or control unit, and controls the overall operation or part of the operation of each component based on various programs recorded in the ROM 202, RAM 203, storage unit 208, or removable recording medium 501.

[0064] ROM202 is a means of storing programs loaded into CPU201 and data used for calculations. RAM203 temporarily or permanently stores, for example, programs loaded into CPU201 and various parameters that change as needed when executing those programs.

[0065] The CPU 201, ROM 202, and RAM 203 are interconnected via bus 204. Meanwhile, various components are connected to bus 204 via input / output interface 205.

[0066] The control unit 206 receives user input and outputs an operation signal corresponding to the received input to the CPU 201. The control unit 206 may include, for example, a mouse, keyboard, touch panel, buttons, switches, and levers. Furthermore, the control unit 206 may also include a remote controller (hereinafter referred to as a remote control) capable of transmitting control signals using infrared or other radio waves.

[0067] The display unit 207 is composed of a liquid crystal display or an organic EL display and displays various information under the control of the CPU 201. Here, the operation unit 206 and the display unit 207 constitute the user interface.

[0068] The memory unit 208 is a device for storing various types of data. Examples of the memory unit 208 include magnetic storage devices such as hard disk drives (HDDs), semiconductor storage devices, optical storage devices, or magneto-optical storage devices.

[0069] The drive 209 is a device that reads information recorded on a removable recording medium 501, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, or writes information to the removable recording medium 501.

[0070] The removable recording medium 501 may be, for example, DVD media, Blu-ray® media, HD DVD media, or various semiconductor storage media. Of course, the removable recording medium 501 may also be, for example, an IC card equipped with a contactless IC chip, or an electronic device.

[0071] The connection port 210 is a port for connecting external devices 502, such as a USB (Universal Serial Bus) port, IEEE1394 port, HDMI (High-Definition Multimedia Interface) port, SCSI (Small Computer System Interface) port, RS-232C port, or optical audio terminal. Examples of external devices 502 include printers, portable music players, digital cameras, digital video cameras, or IC recorders.

[0072] The communication unit 211 is a communication device for connecting to the network 503, and is, for example, a communication card for wired or wireless LAN, Bluetooth®, or WUSB (Wireless USB), a router for optical communication, a router for ADSL (Asymmetric Digital Subscriber Line), or a modem for various types of communication.

[0073] Regarding the configuration of Cloud Server 300, it will be the same as that of PC200, so we will omit the explanation of that configuration example.

[0074] "Processing on PCs and cloud servers" Figure 5 shows an example of a functional block diagram for PC200 and cloud server 300. The processing in PC200 and cloud server 300 will be further explained with reference to this functional block.

[0075] Application 1 of PC200 includes a RAW development unit 211 and a file generation unit 212. The RAW development unit 211 performs development processing on the target RAW image, which is a RAW image related to the shooting of a subject, to obtain an output image. This target RAW image can be obtained, for example, by reading it from a removable recording medium 501 (see Figure 4).

[0076] In connection with this development process, image quality adjustments are made based on the user's image quality adjustment operations, and the image is developed to achieve the user's preferred image quality. The user can perform operations such as color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment.

[0077] The display unit 207 displays the output image obtained after the development process. The image quality of this output image changes according to the user's image quality adjustment operations. Therefore, the user can refer to the output image displayed on the display unit 207 and adjust the image quality to obtain their preferred quality. The display unit 207 also displays a UI for the user's image quality adjustment operations. Based on this UI display, the user can easily and appropriately perform image quality adjustment operations.

[0078] Here, the image quality adjustment history is stored. This history includes information on which adjustment items were adjusted, in what order, and to what extent. The reason for storing the image quality adjustment history, rather than the final adjustment value for each item, is to use this history as image quality adjustment information so that Application 2 can perfectly reproduce the image quality adjustments made in Application 1. This takes into account that the adjustment results may change depending on the order in which each adjustment item is adjusted.

[0079] Furthermore, in image quality adjustment operations performed by the user, it is also possible to perform image quality adjustment operations (fine-tuning of image quality) starting from a certain adjustment result to obtain the final adjustment result. In this case, for a certain adjustment result, the image quality adjustment history at the time that result was obtained and the target RAW image are saved in association. Then, when the user performs adjustment operations starting from a certain adjustment result, the image quality adjustment is performed on the saved target RAW image based on the saved image quality adjustment history, and a certain adjustment result is reproduced. The user can then perform image quality adjustments from that state to obtain the final adjustment result. In this case, the new image quality adjustment history is added to the saved image quality adjustment history and becomes the final image quality adjustment history.

[0080] The file generation unit 212 generates an image file (JPG file) based on the YC signal output from the RAW development unit 211. This image file is recorded on the removable recording medium 501 by the drive 209, and can be played back as needed for, for example, image display or transmitted to an external device.

[0081] Application 1 notifies Application 2 of image quality adjustment information in response to the press of the "Apply to Camera" button displayed on the PC200's display unit 207 (see Figure 4). This adjustment information includes the history of the image quality adjustments described above. It is also possible to include the final adjustment values ​​for each adjustment item in this image quality adjustment information instead of the history of image quality adjustments.

[0082] Application 2 of PC200 includes a RAW development unit 221 and a file generation unit 222. The RAW development unit 221 has the same configuration as the RAW development unit 221 in Application 1. The RAW development unit 221 performs development processing on the RAW image to be analyzed (a RAW image suitable for analysis) to obtain an adjusted image to be analyzed as an output image. This RAW development unit 221 constitutes the image quality adjustment unit for the image to be analyzed.

[0083] The RAW image to be analyzed is obtained by reading it from memory 213. This memory 213 is composed of, for example, RAM 203 (see Figure 4). Application 2 (PC200) retrieves the RAW image to be analyzed from the RAW image memory 301 of the cloud server 300 and stores it in memory 213.

[0084] Here, by using a RAW image for analysis in Application 2 that matches the shooting conditions (ISO sensitivity, aperture, shutter speed, and camera model, etc.) of the RAW image to be adjusted in Application 1, the accuracy of the image quality setting parameters determined by the cloud server 300 can be improved. In particular, by matching the ISO sensitivity, the noise level of the final image can be matched.

[0085] Therefore, in Application 2, the RAW development unit 221, which constitutes the image quality adjustment unit for the image to be analyzed, selects the RAW image to be analyzed from a plurality of candidate RAW images for analysis, which are candidates for the RAW image to be analyzed, stored in the RAW image memory 301 of the cloud server 301, based on the shooting condition information that indicates the shooting conditions of the RAW image to be adjusted. In this case, for example, the RAW image to be adjusted has shooting condition information attached to it, and the plurality of RAW images to be analyzed stored in the RAW image memory 301 also have shooting condition information attached to them.

[0086] In this case, it is conceivable that the RAW image to be analyzed in Application 2 may not be one that perfectly matches the shooting conditions of the RAW image to be adjusted in Application 1.

[0087] Let's explain what happens when the ISO sensitivity is incorrect. For example, suppose a user applies strong noise reduction to a noisy RAW image taken at a high ISO of 50000 to achieve their desired image. If the RAW image being analyzed was taken at a low ISO of 100, applying the same noise reduction would result in an image with significantly degraded resolution.

[0088] In this case, the solution is to offer the user the option to choose which adjustments to apply. For example, you could recommend that users not apply sharpness and noise adjustments, which primarily affect resolution and noise levels due to ISO sensitivity. On the other hand, in this case, color adjustments, brightness adjustments, contrast adjustments, and various effects, which significantly impact the overall image impression, should be applied.

[0089] Next, we will explain the case where either or both of the RAW images to be adjusted or analyzed lack shooting condition information, and their characteristics are unknown. In this case, there are similar concerns as when the ISO sensitivity is incorrect, as mentioned above. Therefore, this can be resolved by offering the user the option to choose which adjustment items to apply. It is also possible to recommend that users not apply sharpness adjustments and noise adjustments, which mainly affect the perceived resolution and noise level due to the characteristics of the RAW image being adjusted. On the other hand, in this case, color adjustments, brightness adjustments, contrast adjustments, and various effects, which affect the overall impression of the image, should be applied.

[0090] The file generation unit 222 generates an image file (JPG file) based on the adjusted analysis target image (YC signal) output from the RAW development unit 221. Application 2 sends this image file to the cloud server 300 to calculate (determine) the image quality setting parameters of the captured image acquired by the camera 100. In this case, it is also possible to send the YC signal instead of a JPG file.

[0091] The cloud server 300 includes a RAW image memory 301 for analysis, a RAW development unit 302, and a parameter calculation unit 303. The parameter calculation unit 303 includes an image evaluation system 304 and an automatic tuning system 305 for image quality setting parameters.

[0092] The RAW development unit 302 has the same configuration as the RAW development unit 114 of the camera 100 (see Figure 3). The RAW development unit 302 acquires the same RAW image to be analyzed used in application 2 of the PC 200 from the RAW image memory 301, performs development processing, and obtains an adjusted image as the output image (YC signal).

[0093] The parameter calculation unit 303 calculates (determines) the image quality setting parameters to be set in the RAW development unit 302 based on the adjusted image from the RAW development unit 302 and the image file (JPG file) of the adjusted image to be analyzed sent from application 2 on the PC 200. In this case, the image quality setting parameters are calculated (determined) so that the difference between the image quality evaluation value of the adjusted image (first image quality evaluation value) and the image quality evaluation value of the adjusted image to be analyzed (second image quality evaluation value) is less than or equal to a predetermined value.

[0094] The image quality evaluation system 304 evaluates the image quality of the adjusted image and the adjusted image to be analyzed, and obtains a first image quality evaluation value and a second image quality evaluation value, respectively. The image quality evaluation system 304 then calculates an image quality difference index that shows the difference between the first image quality evaluation value and the second image quality evaluation value. Here, the first image quality evaluation value and the second image quality evaluation value are evaluation values ​​that evaluate at least one of the following: color reproduction, contrast, resolution, and noise level. This makes it possible to determine the image quality setting parameters so that at least one of the image quality aspects of color reproduction, contrast, resolution, and noise level is matched.

[0095] The image quality setting parameter automatic tuning system 305 uses nonlinear optimization algorithms such as genetic algorithms (GA) and simulated annealing (SA) to calculate provisional image quality setting parameters for the RAW development unit 302, based on the image quality difference index (e.g., structural similarity) calculated by the image quality evaluation system 304, so as to minimize the difference. The provisional image quality setting parameters obtained by the image quality setting parameter automatic tuning system 305 are reflected in the RAW development unit 302.

[0096] The image quality setting parameter automatic tuning system 305 repeatedly determines provisional image quality setting parameters for the RAW development unit 302 based on a new image quality difference index, optimizes the process, and calculates the image quality setting parameters. In this case, for example, if the image quality difference index exceeds a threshold, the provisional image quality setting parameters are saved as image quality setting parameters. Manually adjusting the image quality setting parameters is extremely time-consuming, but by using this system, image quality setting parameters can be calculated (determined) accurately without manual intervention.

[0097] The cloud server 300 transmits parameter information, which is information about the image quality setting parameters calculated (determined) by the image quality setting parameter automatic tuning system 305, to the PC 200. The PC 200 takes this parameter information into memory 213 and then sends it to camera 100 via application 1. Note that the parameter calculation unit 303 in the cloud server 300 is not limited to being composed of the image quality evaluation system 304 and the image quality setting parameter automatic tuning system 305 as described above.

[0098] "Example of display on a PC" Figure 6 shows an example of the display on the PC200's display unit 207 (see Figure 4). Arrow P1 indicates the display area of ​​the output image. Arrow P2 indicates the UI display area for image quality adjustment operations. In this example, the user can perform color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment operations based on the UI display, and can also select various effects.

[0099] As shown in Figure 7, the user can adjust each parameter in the UI display area P1 for image quality adjustment to achieve the desired image quality of the output image. If, as a result of the image quality adjustment operation, the output image quality is to the user's liking and they want to reflect that quality to the camera 100, the user selects "Reflect to Camera" from the "File" pull-down menu, as shown in Figure 8. This causes a "Reflect to Camera" button to appear on the display unit 207, as shown in Figure 9, for reflecting the parameters to the camera 100.

[0100] When the user presses the "Reflect to Camera" button, the process proceeds to the processing of application 2 on PC200, and then to the calculation of image quality setting parameters on the cloud server 300, as described above. In this case, as shown in Figure 10, a progress bar is displayed that shows the progress until the image quality setting parameters are calculated on the cloud server 300. This progress bar allows the user to know the progress of the processing.

[0101] When the cloud server 300 has finished calculating the image quality setting parameters, as shown in Figure 11, the progress bar on the display unit 207 will display "Complete!!", and a "Send Settings" button will appear to send the image quality setting parameters calculated by the cloud server 300 to the camera 100 for setting. When the progress bar displays "Complete!!", for example, the image quality setting parameters calculated by the cloud server 300 have been sent from the cloud server 300 to the PC 200 and stored in the memory 213.

[0102] Furthermore, when the user sets image quality setting parameters in the RAW development unit 114 of the camera 100, it is possible to select one setting from among several settings. When the image quality setting parameters calculated by the cloud server 300 are sent from the PC 200 to the camera 100 as described above, the camera 100 is pre-configured by the user to select which setting to retain for the image quality setting parameters sent from the PC 200.

[0103] Figure 12(a) shows an example of the camera settings menu displayed on the display unit 104 of the camera 100. The user checks which setting to import the image quality setting parameters into in this camera settings menu. In the example shown, the checkbox for "Import to setting 1" is checked. After checking which setting to import the image quality setting parameters into, when the user presses down the "Import" button, the camera settings menu displays "Import standby OK" as shown in Figure 12(b).

[0104] As shown in Figure 12(c), when the camera 100 is in the "import standby OK" state and the user presses the "Send Settings" button displayed on the display unit 207 of the PC 200, the import of image quality setting parameters from the PC 200 to the camera 100 begins. At this time, a progress bar is displayed in the camera settings menu, as shown in Figure 12(d). This progress bar allows the user to see the progress of the import. When the import is complete, the camera settings menu displays "Import Complete!!" as shown in Figure 12(e), and the user knows that the import of image quality setting parameters from the PC 200 to the camera 100 is complete.

[0105] As mentioned above, when "Reflect to Camera" is selected from the "File" pull-down menu on the PC200's display unit 207 (see Figure 8), an example was shown in Figure 9 where only the "Reflect to Camera" button is displayed on the PC200's display unit 207.

[0106] However, as shown in Figure 13, it is also conceivable to display additional checkboxes that allow the user to select which image quality adjustment items, among the multiple image quality adjustment items operated by the user in relation to RAW development in Application 1, should be reflected in Application 2. In the example shown, the checkboxes for "Color Adjustment," "Brightness Adjustment," and "Contrast Adjustment" are checked. This allows the user to arbitrarily select which image quality adjustment items to reflect in Application 2, and the image quality corresponding to the image quality adjustment items selected by the user can be reflected in Camera 100.

[0107] Furthermore, if the user can select the image quality adjustment items to be reflected in Application 2, the RAW development unit 221, which constitutes the image quality adjustment unit for analysis, may select the RAW image to be analyzed for use in Application 2 according to the image quality adjustment items selected by the user, and have the cloud server 300 calculate (determine) image quality setting parameters to accurately reflect the image quality corresponding to the image quality adjustment items selected by the user to the camera 100. For example, if the image quality corresponding to the image quality adjustment item selected by the user is color reproduction, the RAW image to be analyzed for use in Application 2 will include an image region that can accurately evaluate color reproduction.

[0108] As explained above, in the information processing system 10 shown in Figure 1, application 2 of PC 200 performs image quality adjustment on the RAW image to be analyzed based on image quality adjustment information indicating the image quality adjustment values ​​for the RAW image to be adjusted. This generates an adjusted image to be analyzed that is used together with the RAW image to be analyzed to determine the image quality setting parameters of the captured image acquired by camera 100. Therefore, the image quality setting parameters of the captured image can be determined using the RAW image to be analyzed and the adjusted image to be analyzed, and the user's preferred image quality can be reflected in camera 100 with greater accuracy.

[0109] In Figure 5, the functional block diagram of PC200 and cloud server 300 shows an example where image quality setting parameters calculated by the cloud server 300 are sent to camera 200 via PC200. However, it is also possible to send the image quality setting parameters calculated by the cloud server 300 directly to camera 100 via network 400. Figure 14 shows an example of a functional block diagram of PC200 and cloud server 300 in that case. In Figure 14, parts corresponding to those in Figure 5 are denoted by the same reference numerals, and their detailed explanations are omitted.

[0110] Furthermore, as described above, in PC200, Application 2 performs development processing on the RAW image to be analyzed based on the image quality adjustment information obtained in Application 1 to generate an adjusted image to be analyzed. However, it is also conceivable that this processing in Application 2 could be performed in Application 1. In this case, the processing of Application 1 and Application 2 can be handled by a single application (program).

[0111] In this case, for example, application 2 is integrated into application 1, and when the user presses the "Apply to Camera" button, the adjusted image to be analyzed, obtained by processing the RAW image to be analyzed, is sent to the cloud server 300 and used to calculate image quality setting parameters. Here, the application of image quality adjustment items in the processing of the RAW image to be analyzed may be performed in parallel with the application of image quality adjustment items in the processing of the RAW image to be adjusted until the "Apply to Camera" button is pressed, or all adjustments may be applied at once based on the adjustment history when the "Apply to Camera" button is pressed.

[0112] Furthermore, although not mentioned above, Application 1 on the PC200 functions as a normal RAW editing application unless the "Reflect to Camera" button is pressed. The display and hiding of the "Reflect to Camera" button can also be toggled.

[0113] Also, although not mentioned above, you can press the "Reflect to Camera" button whenever you feel that you have reached a certain level of completion during the editing process. You can create multiple candidates by making minor adjustments to the adjustment items that are already at a certain level of completion, or you can create completely different variations.

[0114] Furthermore, although not mentioned above, the RAW images to be analyzed used in Application 2 can be updated as needed, such as when updating Application 1, to facilitate the calculation of image quality setting parameters on the cloud server 300.

[0115] Furthermore, as described above, the image quality adjustments in the development process of Application 1 are performed by the user on PC200, but it is also conceivable that this part be performed by a professional or creator. Alternatively, the processing of Application 1 could be performed by an external device, and the image quality adjustment information could be supplied to PC200 from the external device.

[0116] Furthermore, as described above, each time the "Apply to Camera" button is pressed on the PC200, the image quality setting parameters generated on the cloud server 300 are imported as pre-selected settings (see Figure 12).

[0117] As a result, as shown in Figure 15, the camera 100 can store image quality setting parameters for multiple settings in memory 102. In this state, the user selects the desired image quality setting parameters from the camera setting menu displayed on the camera's display unit 104 and sets them in the RAW development unit 104 for use. In the illustrated example, the state in which "Setting 1: xxx setting" is selected is shown. In this case, the user can arbitrarily name each setting in the camera setting menu.

[0118] In this case, instead of storing image quality setting parameters for multiple settings in memory 102, it is also possible to store them in the cloud server 300, as shown in Figure 16, and when the user selects the desired image quality setting parameters from the camera setting menu displayed on the camera's display unit 104, those image quality setting parameters are retrieved from the cloud server 300 to the camera 100 and set in the RAW development unit 104 for use. By storing them in the cloud server 300 in this way, the capacity of the camera's memory 102 can be reduced.

[0119] <2. Variant> In the above-described embodiment, the type of image content of the RAW image to be adjusted is not taken into consideration. Users can expect that the optimal processing will not be the same every time for each RAW image to be adjusted, but will vary depending on the situation. Possible conditions that may cause this variation include: (1) the subject (people, landscapes, nightscapes, etc.), (2) the expression of emotion (warm colors, cool colors, high contrast, low contrast, etc.), and (3) the nature of the image itself (noise level, resolution level, colorfulness, lack of color, etc.).

[0120] In this case, the cloud server 300 calculates (determines) image quality setting parameters for each image type information indicating the type of image content of the RAW image to be adjusted, and the camera 100 sets the image quality setting parameters according to the type of image content of the captured image in the RAW development unit 114, making them available for use. This allows different image quality adjustment processing to be reflected in the camera 100 for each type of image content of the RAW image to be adjusted. Here, by including information indicating the type of subject in the image type information, different image quality adjustment processing can be reflected in the camera 100 for each type of subject.

[0121] In this case, by associating the adjusted analysis target image generated by Application 2 with image type information (metadata) indicating the type of image content of the adjustment target RAW image, different image quality adjustment processes can be applied to Camera 100 for each type of image content of the adjustment target RAW image.

[0122] If the calculation (determination) of image quality setting parameters is performed for each image type information indicating the type of image content of the RAW image to be adjusted, a possible solution is to change the image quality setting parameters set in the RAW development unit 114 of the camera 100 in conjunction with the subject recognition function of the camera 100.

[0123] First, we will explain the case where the user manually associates the RAW image to be adjusted with the type of subject. In this case, as schematically shown in Figure 17, the user selects which type of subject to associate with the "Reflect Camera" button on the PC200 by pressing down the corresponding button. In the example shown, the user has selected that the type of subject is a person, and the "Reflect Camera (Person)" button has been pressed down.

[0124] In this case, when image quality adjustment information is notified from Application 1 to Application 2, image type information (metadata) indicating the type of subject is added to this image quality adjustment information. Then, when Application 2 performs RAW development processing on the RAW image to be analyzed, it performs image quality adjustment processing based on the image quality adjustment information notified from Application 1, and an adjusted image to be analyzed is generated. This adjusted image to be analyzed also has the aforementioned image type information (metadata) indicating the type of subject added to it.

[0125] Application 2 sends the adjusted images to be analyzed, with image type information (metadata) indicating the type of subject attached, to the cloud server 300. The cloud server 300 then generates image quality setting parameters for each type of subject. These image quality setting parameters generated by the cloud server 300, with image type information (metadata) indicating the type of subject attached, are then sent to the camera 100 and stored for each type of subject.

[0126] In camera 100, subject recognition processing is performed, and image quality setting parameters corresponding to the recognized subject are read and set in the RAW development unit 114 for use. This allows image quality adjustment processing according to the type of subject to be reflected in camera 100.

[0127] The flowchart in Figure 18 schematically shows the processing flow when, for example, the user manually associates the RAW image to be adjusted with the type of subject (person).

[0128] In step ST1, Application 1 performs RAW development processing on the RAW image to be adjusted. During this process, the user performs image quality adjustments. Next, in step ST2, in Application 1, the user determines that the subject is a person and selects and presses the "Reflect on camera (person)" button.

[0129] Next, in step ST3, application 2 performs RAW development processing on the RAW image to be analyzed based on the image quality adjustment information notified from application 1. This generates an adjusted image to be analyzed that corresponds to the subject (person). Next, in step ST4, the automatic image quality setting parameter tuning system calculates (determines) the image quality setting parameters corresponding to the subject (person). These image quality setting parameters are sent to and stored in camera 100.

[0130] Next, in step ST5, the camera 100 recognizes the subject as a person. Then, in step ST6, the camera 100 sets the image quality setting parameters corresponding to the subject (person) in the RAW development unit 114, performs RAW development using those image quality setting parameters, and obtains the captured image.

[0131] Next, we will explain the case where the mapping between the RAW image to be adjusted and the type of subject is performed automatically. In this case, the type of subject is identified based on the image type information (metadata) attached to the RAW image to be adjusted, or the subject type recognition processing information for the RAW image to be adjusted in Application 1.

[0132] In this case, as schematically shown in Figure 19, the corresponding "Camera Reflection" button will be explicitly displayed in a different state from the others, based on the identification result of the subject type. In the illustrated example, the state in which the subject type has been automatically identified as a person is shown. In this case, only the "Camera Reflection" button corresponding to the automatically identified subject type may be displayed.

[0133] When performing the camera reflection operation on the PC200, the user presses the "Camera Reflection" button corresponding to the automatically identified subject type. Subsequent operations are the same as when the user manually associates the adjustment target RAW image with the subject type as described above.

[0134] The flowchart in Figure 20 schematically shows the processing flow when, for example, the matching of the RAW image to be adjusted with the type of subject (person) is performed automatically.

[0135] In step ST11, Application 1 identifies the type of subject. Next, in step ST12, Application 1 performs RAW development processing on the RAW image to be adjusted. During this process, image quality adjustments are made by the user. Next, in step ST3, the user presses the "Reflect on camera (person)" button in Application 1, which is compatible with automatic identification.

[0136] Next, in step ST14, application 2 performs RAW development processing on the RAW image to be analyzed based on the image quality adjustment information notified from application 1. This generates an adjusted image to be analyzed that corresponds to the subject (person). Next, in step ST15, the automatic image quality setting parameter tuning system calculates (determines) the image quality setting parameters corresponding to the subject (person). These image quality setting parameters are sent to and stored in camera 100.

[0137] Next, in step ST16, the camera 100 recognizes the subject as a person. Then, in step ST17, the camera 100 sets the image quality setting parameters corresponding to the subject (person) in the RAW development unit 114, performs RAW development using those image quality setting parameters, and obtains the captured image.

[0138] In the above example, we showed that camera 100 can have image quality setting parameters according to the type of subject, but it is also conceivable that camera 100 could have image quality setting parameters that correspond to even more types of image content.

[0139] In this case, as schematically shown in Figure 21, when the user performs the camera reflection operation on the PC200, they press the "Reflect to Camera" button, which defines the type of image content to be reflected. In this case, the user can define the type of image content for each button and change the definition as needed. Here, the type of image content can include not only the subject as described above, but also expressions of emotion, the properties of the image itself, etc.

[0140] When a predetermined "Reflect to Camera" button, which defines the type of image content, is pressed, and image quality adjustment information is notified from Application 1 to Application 2, image type information (metadata) indicating the type of image content is added to this image quality adjustment information. Then, when Application 2 performs RAW development processing on the RAW image to be analyzed, it performs image quality adjustment processing based on the image quality adjustment information notified from Application 1, and an adjusted image to be analyzed is generated. This adjusted image to be analyzed also has the aforementioned image type information (metadata) indicating the type of image content added to it.

[0141] Application 2 sends the adjusted images to be analyzed, with image type information (metadata) indicating the type of image content attached, to the cloud server 300. The cloud server 300 then generates image quality setting parameters for each type of image content. These image quality setting parameters generated by the cloud server 300, with image type information (metadata) indicating the type of image content attached, are then sent to the camera 100 and stored for each type of image content.

[0142] In camera 100, the user selects the image quality setting parameters corresponding to the desired image content type from a set of image quality setting parameters, and sets them in the RAW development unit 114. This allows camera 100 to perform RAW development based on the image quality setting parameters desired by the user and obtain an image.

[0143] The flowchart in Figure 22 schematically shows the processing flow when, for example, a user selects a predetermined type of image content and the camera 100 uses image quality setting parameters corresponding to that predetermined type of image content.

[0144] In step ST21, RAW development processing is performed on the RAW image to be adjusted. During this process, image quality adjustments are made by the user. Next, in step ST22, in application 1, the user selects and presses the "Reflect to Camera" button, which has a defined type of image content. The illustrated example shows the case where the "Reflect to Camera (× Corresponding)" button is selected.

[0145] Next, in step ST23, application 2 performs RAW development processing on the RAW image to be analyzed based on the image quality adjustment information notified from application 1. This generates an adjusted image to be analyzed corresponding to a predetermined type of image content. Next, in step ST24, the automatic image quality setting parameter tuning system calculates (determines) the image quality setting parameters corresponding to a predetermined type of image content. These image quality setting parameters are sent to and held by camera 100.

[0146] Next, in step ST25, the user selects an image quality setting parameter corresponding to a predetermined type of image content on the camera 100 and sets it on the RAW development unit 114. Then, in step ST26, the camera 100 performs RAW development using the image quality setting parameter corresponding to the predetermined type of image content to obtain the captured image.

[0147] Furthermore, the above-described embodiment showed an example in which PC200 has application 1 and application 2. However, an example in which application 2 resides on the cloud server 300 is also conceivable.

[0148] Figure 23 shows an example of a functional block diagram of PC200 and cloud server 300 in that case. In Figure 23, parts corresponding to those in Figures 5 and 14 are denoted by the same reference numerals. In this example in Figure 23, the configuration is the same as in the example in Figure 14, except that application 2 has moved from PC200 to cloud server 300, so a detailed explanation is omitted.

[0149] In the example shown in Figure 23, the image quality setting parameters calculated by the cloud server 300 are directly transmitted to the camera 100 via the network 400. However, as shown in the example in Figure 5, it is also possible to transmit the image quality setting parameters calculated by the cloud server 300 to the camera 200 via the PC 200.

[0150] Furthermore, in the example shown in Figure 23, the system has a separate image quality setting parameter determination unit (RAW development unit, parameter calculation unit 303) that determines image quality setting parameters independently of Application 2. However, it is also possible to include this image quality setting parameter determination unit within Application 2. In this case, the processing of Application 2 and the processing of determining image quality setting parameters can be handled by a single application (program).

[0151] Furthermore, the above-described embodiment showed an example in which PC200 has application 1 and application 2. However, an example in which application 1 and application 2 reside on the cloud server 300 is also conceivable.

[0152] Figure 24 shows an example of a functional block diagram of PC200 and cloud server 300 in that case. In Figure 24, parts corresponding to those in Figures 5 and 14 are denoted by the same reference numerals. In this example in Figure 24, the configuration is the same as in the example in Figure 14, except that applications 1 and 2 have moved from PC200 to cloud server 300, so a detailed explanation is omitted.

[0153] In the example shown in Figure 24, the image quality setting parameters calculated by the cloud server 300 are directly transmitted to the camera 100 via the network 400. However, as shown in the example in Figure 5, it is also possible to transmit the image quality setting parameters calculated by the cloud server 300 to the camera 200 via the PC 200.

[0154] Furthermore, while preferred embodiments of this disclosure have been described in detail with reference to the accompanying drawings, the technical scope of this disclosure is not limited to such examples. It is clear to any person with ordinary skill in the art of this disclosure that various modifications or alterations may be conceived within the scope of the technical idea set forth in the claims, and these too will naturally fall within the technical scope of this disclosure.

[0155] Furthermore, the effects described herein are merely descriptive or illustrative and not limiting. In other words, the technology relating to this disclosure may produce other effects that will be apparent to those skilled in the art from the description herein, in addition to or in lieu of the effects described herein.

[0156] Furthermore, this technology can also be configured as follows: (1) The computer functions as an analysis target image quality adjustment unit, which generates an adjusted analysis target image used together with the analysis target RAW image for determining the image quality setting parameters of the captured image acquired by the imaging device, by performing image quality adjustment on an analysis target RAW image different from the adjustment target RAW image based on image quality adjustment information indicating the image quality adjustment values ​​of the image quality adjustment process for the adjustment target RAW image. program. (2) The image quality adjustment information includes information indicating at least one adjustment value from among color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment. The program described in (1) above. (3) The analysis target image quality adjustment unit generates the adjusted analysis target image by performing the same image quality adjustment process on the analysis target RAW image as the image quality adjustment process on the adjustment target RAW image. The program described in (1) or (2) above. (4) The image quality adjustment information is information that indicates the adjustment values ​​of multiple image quality adjustment items, The aforementioned image quality adjustment unit generates the adjusted image to be analyzed based on selected image quality adjustment information, which indicates the adjustment values ​​of the image quality adjustment items selected by the user from among the plurality of image quality adjustment items. The program described in any of (1) to (3) above. (5) The RAW image to be analyzed is an image provided by an external device different from the device equipped with the computer. The program described in any of (1) to (4) above. (6) The image quality adjustment information is information that indicates the adjustment values ​​of multiple image quality adjustment items, The aforementioned RAW image to be analyzed has multiple image regions, Each of the plurality of image regions corresponds to at least one of the plurality of image quality adjustment items. The program described in any of (1) to (5) above. (7) The analysis target image quality adjustment unit generates the adjusted analysis target image based on the image quality adjustment information in response to the user's operation to reflect image quality settings. The program described in any of (1) to (6) above. (8) The analysis target image quality adjustment unit associates the adjusted analysis target image with image type information indicating the type of image content of the adjustment target RAW image. The program described in any of (1) to (7) above. (9) The image quality setting parameters are determined for each image type information indicating the type of image content of the RAW image to be adjusted. The program described in any of (1) to (8) above. (10) The image type information includes information indicating the type of subject, The program described in (8) or (9) above. (11) The analysis target image quality adjustment unit selects the analysis target RAW image from a plurality of candidate analysis target RAW images, which are candidates for the analysis target RAW image, based on shooting condition information indicating the shooting conditions of the adjustment target RAW image. The program described in any of (1) to (10) above. (12) The computer is made to function as an image quality setting parameter determination unit that determines the image quality setting parameters based on the RAW image to be analyzed and the adjusted image to be analyzed. The program described in any of (1) through (11) above. (13) The image quality setting parameter determination unit determines the image quality setting parameters such that the difference between a first image quality evaluation value indicating the evaluation of the image quality of the adjusted image generated by performing image quality adjustment processing on the RAW image to be analyzed based on the image quality setting parameters and a second image quality evaluation value indicating the evaluation of the image quality of the adjusted image to be analyzed is less than or equal to a predetermined value. The program described in (12) above. (14) The first image quality evaluation value and the second image quality evaluation value are evaluation values ​​that evaluate at least one of the following: color reproduction, contrast, resolution, and noise level. The program described in (13) above. (15) The computer is made to function as an adjustment target image quality adjustment unit that performs image quality adjustment processing on the adjustment target RAW image based on the image quality adjustment information. A program as described in any of (1) through (14) above. (16) The image quality adjustment value is determined by the user's image quality adjustment operation on the RAW image to be adjusted. The program described in any of (1) to (15) above. (17) The system includes an analysis target image quality adjustment unit that generates an adjusted analysis target image to be used together with the analysis target RAW image for determining the image quality setting parameters of the captured image acquired by the imaging device, by performing image quality adjustment processing on an analysis target RAW image different from the adjustment target RAW image based on image quality adjustment information indicating the image quality adjustment values ​​of the image quality adjustment processing for the adjustment target RAW image, Information processing device. (18) The analysis target image quality adjustment procedure has an analysis target image quality adjustment procedure which is used together with the analysis target image to determine the image quality setting parameters of the captured image acquired by the imaging device by performing an image quality adjustment procedure on an analysis target RAW image different from the adjustment target RAW image based on image quality adjustment information that indicates the image quality adjustment values ​​of the image quality adjustment procedure on the adjustment target RAW image, Information processing methods. (19) Having an information processing device and a server, The aforementioned information processing device is The system includes an analysis target image quality adjustment unit that generates an adjusted analysis target image used together with the analysis target RAW image for determining the image quality setting parameters of the captured image acquired by the imaging device, by performing image quality adjustment processing on an analysis target RAW image different from the adjustment target RAW image based on image quality adjustment information indicating the image quality adjustment values ​​for the image quality adjustment processing on the adjustment target RAW image, The aforementioned server, The system includes a picture quality setting parameter determination unit that determines the picture quality setting parameters based on the RAW image to be analyzed and the adjusted image to be analyzed generated by the picture quality adjustment unit. Information processing system. [Explanation of symbols]

[0157] 10. Information Processing Systems 100...camera 101... Control Unit 102...memory 103...Operation unit 104...Display section 105...Recording / Playback Unit 106... Communications Department 111...Optical system 112...Imager 113...RAW Data Processing Unit 114...Developing and processing unit 115...JPG generation section 116...RAW generation section 121...Brightness adjustment section 122... Simultaneous Processing Unit 123... White balance adjustment section 124... Sharpness / Noise Adjustment Section 125...Color / Contrast Adjustment Section 126...YC generation section 200...PC 201···CPU 202···ROM 203...RAM 204...bus 205... Input / Output Interface 206...Operation unit 207...Display section 208...Storage section 209... Drive 210... Connection port 211... Communications Department 211...RAW Development Section 212...File generation section 213...memory 221...RAW Development Section 222...File generation section 300...Cloud Servers 301...RAW image memory to be analyzed 302...RAW Development Section 303...Parameter calculation unit 304...Image Quality Evaluation System 305... Automatic tuning system for image quality settings parameters 400 Network 501... Removable recording media 502...External connection devices 503 Network

Claims

1. The computer functions as a processing unit that generates image quality adjustment information corresponding to the type of image content of the RAW image to be adjusted, indicating the image quality adjustment value of the image quality adjustment processing in the first development unit for the RAW image to be adjusted, and generates image quality setting parameters for each type of image content, to be used in the image quality adjustment processing in the second development unit, which has a different configuration from the first development unit, for the captured RAW image acquired by the imaging device. program.

2. The processing unit further performs a process to identify the type of image content of the RAW image to be adjusted. The program according to claim 1.

3. The processing unit further performs the process of transmitting the image quality setting parameters to the imaging device, along with image type information indicating the type of image content. The program according to claim 1.

4. The processing unit performs image quality adjustment processing on a RAW image to be analyzed that is different from the RAW image to be adjusted, using a third development unit having the same configuration as the first development unit, based on the image quality adjustment information, to generate an adjusted image to be analyzed. The processing unit then performs image quality adjustment processing on the adjusted image to be analyzed and the RAW image to be analyzed using a fourth development unit having the same configuration as the second development unit, to generate an adjusted image, and uses the adjusted image to be analyzed to generate the image quality setting parameters. The program according to claim 1.

5. The aforementioned image quality adjustment information includes information indicating at least one adjustment value from among color adjustment, brightness adjustment, tone adjustment, sharpness adjustment, and noise adjustment. The program according to claim 1.

6. The type of image content includes the type of subject, The program according to claim 1.

7. The aforementioned image quality adjustment value is determined by the user's image quality adjustment operation on the RAW image to be adjusted. The program according to claim 1.

8. The system includes a processing unit that generates image quality adjustment information corresponding to the type of image content of the target RAW image, indicating the image quality adjustment value of the image quality adjustment processing in the first development unit for the target RAW image, and that generates image quality setting parameters for each type of image content, to be used in the image quality adjustment processing in the second development unit, which has a different configuration from the first development unit, for the captured RAW image acquired by the imaging device, based on the image quality adjustment information. Information processing device.

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