Image processing method and device, electronic equipment, storage medium and chip

Abstract

The invention provides an image processing method. The method comprises the following steps: acquiring a plurality of input images of multiple channels; marking the plurality of input images to determine a plurality of marked images; determining a superimposed image based on the plurality of marked images; an output image is determined based on the superimposed image and the plurality of tagged images. According to the method disclosed by the invention, a set of image processing engine is adopted to uniformly process the multi-layer image, so that the hardware cost is reduced, and meanwhile, the effect superposition of the multi-layer can be adaptively completed by setting different enhancement effects and enhancement levels, so that the image processing efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of image processing, and in particular to an image processing method and device, electronic equipment, storage medium and chip. Background Art

[0002] With the popularization of smart terminal devices and the development of image processing, users have put forward higher requirements for the image quality obtained from the terminal. Image processing is an important direction in the field of display technology. When the terminal outputs images to users, there are multi-channel layer inputs. Different graphics are superimposed on a certain substrate. Therefore, an image processing method that can uniformly process multi-channel images is needed. Summary of the invention

[0003] The present disclosure provides an image processing method and device, an electronic device, a storage medium and a chip to solve the problems in the related technology, and can adaptively complete the effect superposition of multiple layers while reducing hardware costs and device power consumption.

[0004] A first aspect embodiment of the present disclosure proposes an image processing method, which includes: acquiring multiple input images of multiple channels; marking the multiple input images to determine multiple marked images; determining an overlay image based on the multiple marked images; and determining an output image based on the overlay image and the multiple marked images.

[0005] In some embodiments of the present disclosure, marking multiple input images to determine multiple marked images includes: for each input image, adding one or more marks to determine the marked image of the input image, wherein the mark includes at least one of an image coordinate mark, an image enhancement effect mark, an image enhancement level mark, and a transparency mark.

[0006] In some embodiments of the present disclosure, determining a superimposed image based on multiple tagged images includes: determining a canvas image; determining a position of the tagged image in the canvas image based on image coordinate marks in the tagged image; and superimposing the multiple tagged images on the canvas image to determine the superimposed image, wherein a size of the superimposed image does not exceed a size of the canvas image.

[0007] In some embodiments of the present disclosure, multiple marked images are superimposed on a canvas image to determine the superimposed image, including: determining the overall transparency of the multiple input images and the transparency of each pixel in the multiple input images based on the transparency mark in the marked image; determining the pixel value of each pixel in the multiple input images; determining the pixel value of each pixel of the superimposed image based on the overall transparency of the image, the transparency of each pixel and the pixel value of each pixel.

[0008] In some embodiments of the present disclosure, determining the output image based on the overlay image and the multiple tagged images includes: determining one or more effect tagged images based on the tagged image; and determining the output image based on the overlay image and the one or more effect tagged images.

[0009] In some embodiments of the present disclosure, determining one or more effect marked images based on a marked image includes: determining an effect level value of an image enhancement level mark; determining a mark value for each pixel in a first area of ​​an input image; and determining an effect level mark value for each pixel of the effect marked image based on the effect level value and the mark value.

[0010] In some embodiments of the present disclosure, determining the output image based on the superimposed image and one or more effect marked images includes: using a first marked image among multiple effect marked images to process the superimposed image to determine a first processed image; using a second marked image among multiple effect marked images to process the first processed image until multiple marked images are traversed to obtain the output image.

[0011] A second aspect embodiment of the present disclosure proposes an image processing device, which includes: an acquisition unit, used to acquire an input image; a first determination unit, used to mark multiple input images to determine multiple marked images; a second determination unit, used to determine a superimposed image based on the multiple marked images; and a third determination unit, used to determine an output image based on the superimposed image and the multiple marked images.

[0012] The third aspect embodiment of the present disclosure proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in the first aspect embodiment of the present disclosure.

[0013] The fourth aspect embodiment of the present disclosure proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the method described in the first aspect embodiment of the present disclosure.

[0014] The fifth aspect embodiment of the present disclosure proposes a chip, which includes one or more interfaces and one or more processors; the interface is used to receive signals from a memory of an electronic device and send signals to the processor, the signals include computer instructions stored in the memory, and when the processor executes the computer instructions, the electronic device executes the method described in the first aspect embodiment of the present disclosure.

[0015] In summary, according to the image processing method proposed in the present disclosure, the method includes obtaining multiple input images of multiple channels; marking the multiple input images to determine multiple marked images; determining a superimposed image based on the multiple marked images; and determining an output image based on the superimposed image and the multiple marked images. The scheme of the present disclosure can adaptively complete the superposition of multiple layers of effects by marking and superimposing the multi-channel input images and uniformly processing the superimposed images, while reducing hardware costs and device power consumption.

[0016] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0018] Figure 1 A flowchart of an image processing method provided by an embodiment of the present disclosure;

[0019] Figure 2 A flowchart of an image processing method provided by an embodiment of the present disclosure;

[0020] Figure 3 A flowchart of an image processing method provided by an embodiment of the present disclosure;

[0021] Figure 4 A flowchart of an image processing method provided by an embodiment of the present disclosure;

[0022] Figure 5 A flowchart of an image processing method provided by an embodiment of the present disclosure;

[0023] Figure 6 A flowchart of an image processing method provided by an embodiment of the present disclosure;

[0024] Figure 7 A flowchart of an image processing method provided by an embodiment of the present disclosure;

[0025] Figure 8 A flowchart of an image processing method provided by an embodiment of the present disclosure;

[0026] Fig. 9 A schematic diagram of the structure of an image processing device provided by an embodiment of the present disclosure;

[0027] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure;

[0028] Fig.11A schematic diagram of the structure of a chip provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0029] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0030] With the popularization of intelligent terminal devices and the development of image processing, people's technical requirements for terminals are also rising. Image processing technology, as one of the most commonly used technologies, has attracted much attention. Image processing is an important direction in the field of image enhancement. When the terminal outputs images to users, there are multi-channel layer inputs. Different graphics are superimposed on a certain base. Therefore, an image processing method that can uniformly process multi-channel images is needed.

[0031] Due to the increasing requirements for imaging technology in smart terminal devices and smart cars in the Internet of Things, for multi-channel input images, image enhancement processing of different dimensions is required according to product requirements to improve the final image quality. In the related art, for the processing of multi-channel input images, it is necessary to set up a separate processing module for each channel to perform effect processing, and then perform canvas-based superposition. For hardware implementation, this solution requires setting up multiple repeated effect processing modules for each channel, which seriously increases the hardware cost and consumes a lot of power.

[0032] Therefore, in order to solve the problems existing in the related art, the present disclosure proposes an image processing method, which obtains multiple input images of multiple channels; marks the multiple input images to determine multiple marked images; determines a superimposed image based on the multiple marked images; and determines an output image based on the superimposed image and the multiple marked images. A set of image processing engines is used to uniformly process multiple layers.

[0033] This solution uses an image processing engine to uniformly process multiple layers, reducing hardware costs. At the same time, it can adaptively superimpose multiple layers by setting different enhancement effects and enhancement levels, thereby improving image processing efficiency.

[0034] The embodiments of the present disclosure are not exhaustive, but are only illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined, for example, some or all of the steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0035] In each embodiment of the present disclosure, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between the embodiments are consistent and can be referenced to each other, and the technical features in different embodiments can be combined to form a new embodiment based on their internal logical relationships.

[0036] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0037] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular form, such as "a", "an", "the", "above", "said", "aforementioned", "this", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun after the article may be understood as a singular expression or a plural expression.

[0038] In some embodiments, terms such as "in response to ...", "in response to determining ...", "in the case of ...", "at the time of ...", "when ...", "if ...", "if ...", etc. can be used interchangeably.

[0039] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not lower than", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "no more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0040] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only for distinguishing different description objects and do not constitute any restrictions on the position, order, priority, quantity or content of the description objects. For the statement of the description objects, please refer to the description in the context of the claims or embodiments, and no unnecessary restrictions should be constituted due to the use of prefixes.

[0041] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0042] In the embodiments of the present disclosure, terms such as "import", "input", and "read in" can be used interchangeably.

[0043] In some embodiments, devices, etc. can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as "device", "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", and "subject" can be used interchangeably.

[0044] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal" "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client and the like can be used interchangeably.

[0045] Figure 1 This is a flow chart of an image processing method provided by an embodiment of the present disclosure. The method can be applicable to application scenarios such as smart terminals, for example, executed by a terminal with integrated image processing function or an image processor in the terminal, or executed by other devices suitable for image processing to output multi-layer images, and the present disclosure is not limited thereto. Figure 1 As shown, the image processing method includes steps 101-104.

[0046] Step 101, obtaining a plurality of multi-channel input images.

[0047] In some embodiments of the present disclosure, the terminal may acquire multiple input images of multiple channels to mark the multiple input images.

[0048] In some embodiments of the present disclosure, the formats of the multiple input images obtained are the same, so as to facilitate the labeling of the image pairs. Optionally, in some embodiments, the terminal can read images of any format in multiple channels, such as YUV format images, RGB format images, and ARGB format, and convert them to a unified format, such as ARGB format.

[0049] In some embodiments of the present disclosure, there is no limit on the number of input images for each channel, which may be a single image or an image stream formed by multiple images, that is, a video.

[0050] In some embodiments of the present disclosure, there is no limitation on the number of channels of the read-in image, and the number of channels can be any number greater than 1.

[0051] In some embodiments of the present disclosure, the terminal can import images to different channels based on business needs or preset regulations, so that when the input images are subsequently marked, different marks can be set for different channels to improve the marking rate. The present disclosure does not limit the way of importing images. For example, it can be classified according to content, such as games and animation videos are imported from channel 3; it can be classified according to image resolution, such as the maximum resolution image is imported from channel 0; it can also be classified according to the main screen, such as the main screen, imported from channel 1, etc., so that the terminal can mark the image based on business needs. For example, if the terminal needs to enhance the image of the input game and animation video, the terminal can only mark the image enhancement level of the image output from channel 3 by presetting, thereby improving the marking rate.

[0052] Step 102: label a plurality of input images to determine a plurality of labeled images.

[0053] In some embodiments of the present disclosure, the terminal may mark a plurality of input images to determine a plurality of marked images.

[0054] In some embodiments of the present disclosure, one or more tags may be added to the input image acquired by each channel, which is not limited by the present disclosure.

[0055] In some embodiments of the present disclosure, the mark includes at least one of an image coordinate mark, an image enhancement effect mark, an image enhancement level mark, and a transparency mark.

[0056] Step 103: determining a superimposed image based on the multiple marked images.

[0057] In some embodiments of the present disclosure, the terminal may determine a superimposed image after the multiple tagged images are superimposed based on the multiple tagged images.

[0058] Optionally, in some embodiments, the positions of the multiple tagged images in the superimposed image may be determined based on the image coordinate marks in the multiple tagged images.

[0059] Optionally, in some embodiments, the transparency of the multiple tagged images in the superimposed image may be determined based on transparency marks in the multiple tagged images.

[0060] Step 104: determining an output image based on the superimposed image and the plurality of marked images.

[0061] In some embodiments of the present disclosure, the terminal may determine an output image based on the overlay image and the plurality of marker images.

[0062] In some embodiments of the present disclosure, image effect enhancement may be performed on relative pixel points in the overlay image based on image enhancement effect marks and image increase effect level marks in a plurality of marked images to determine an output image.

[0063] In summary, according to the image processing method provided by the present disclosure, the method includes: obtaining multiple input images of multiple channels; marking multiple input images to determine multiple marked images; determining a superimposed image based on the multiple marked images; and determining an output image based on the superimposed image and the multiple marked images. This solution marks multiple input images to determine a superimposed image and multiple marked images, so that a set of image processing engines can be used to uniformly process multi-layer images, thereby reducing hardware costs and device power consumption. At the same time, by setting different enhancement effects and enhancement levels, the effect superposition of multiple layers can be adaptively completed, thereby improving image processing efficiency.

[0064] Figure 2 The following further shows a flowchart of an image processing method proposed in the present disclosure. Figure 1 The embodiment shown further explains step 102. Figure 2 The following steps may be included:

[0065] Step 301: For each input image, one or more tags are added to determine a tagged image of the input image.

[0066] In some embodiments of the present disclosure, the terminal may add one or more tags to each input image to determine a tagged image of the input image. The present disclosure does not limit the number of tags added to each input image.

[0067] In some embodiments of the present disclosure, the mark includes at least one of an image coordinate mark, an image enhancement effect mark, an image enhancement level mark, and a transparency mark.

[0068] Optionally, in some embodiments, image coordinate marks may be added to the input image to mark its position in the superimposed image. For example, the position of the upper left corner pixel of the input image in the superimposed image may be marked, and the position coordinates of other pixels in the superimposed image may be determined by the input image resolution and size.

[0069] Optionally, in some embodiments, an image enhancement effect mark may be added to the input image to mark the enhancement effect required for the image area. The present disclosure does not limit the enhancement effect of the image enhancement effect mark, which may include color enhancement, brightness enhancement, contrast enhancement, etc.

[0070] Optionally, in some embodiments, an image enhancement level mark can be added to the input image to mark the level of the enhancement effect of the image area. The present disclosure does not limit the level of image enhancement, which can be represented by strong, medium, or weak, or by setting an intensity registration table, etc.

[0071] Optionally, in some embodiments, a transparency mark may be added to the input image to mark the transparency of the image area in the superimposed image, wherein the transparency mark may include overall image transparency and local transparency.

[0072] In some embodiments of the present disclosure, the terminal may mark the input image based on business requirements or preset regulations.

[0073] Optionally, in some embodiments, the input image can be marked based on content classification. For example, if the input image is a game or animation video, the image enhancement effect mark is a strong contrast enhancement mark and a weak color enhancement mark; for example, if the input image is a navigation UI image, the image enhancement effect mark is a weak brightness enhancement mark and a medium contrast tone enhancement mark.

[0074] Optionally, in some embodiments, the input image may be marked based on image resolution classification, for example, the larger the input image resolution, the lower the image enhancement level mark.

[0075] In summary, according to the image processing method provided by the present disclosure, the method includes: for each input image, adding one or more marks to determine the marked image of the input image, wherein the mark includes at least one of an image coordinate mark, an image enhancement effect mark, an image enhancement level mark, and a transparency mark. This solution marks multiple input images to determine the position, transparency, enhancement effect, and enhancement level of each input image in the output image, laying the foundation for using a set of image processing engines to uniformly process multi-layer images.

[0076] Figure 3 The following further shows a flowchart of an image processing method proposed in the present disclosure. Figure 1 The embodiment shown further explains step 103. Figure 3 The following steps may be included:

[0077] Step 301, determine the canvas image.

[0078] In some embodiments of the present disclosure, the terminal may determine a canvas to overlay a marker image onto the canvas image, and determine a resolution and size of the overlay image.

[0079] In some embodiments of the present disclosure, the resolution of the canvas image is the resolution of the output image, and the size of the canvas image is less than or equal to the maximum size supported by the output device, such as the display screen size of a smartphone.

[0080] In some embodiments of the present disclosure, the canvas image may be a preset image, and the present disclosure does not limit the canvas image, which may be, for example, a solid color image.

[0081] Step 302: Determine the position of the marked image in the canvas image based on the image coordinate mark in the marked image.

[0082] In some embodiments of the present disclosure, the terminal may determine the position of the marker image in the canvas image based on the image coordinate mark in the marker image, so as to superimpose multiple marker images on the canvas image.

[0083] In some embodiments of the present disclosure, the position coordinates of other pixel points in the superimposed image can be determined by marking the image coordinates in the marked image, and the resolution and size of the marked image.

[0084] In some embodiments of the present disclosure, the marked image can be scaled based on business needs or settings, and the scaled image can be superimposed on the canvas image. The terminal can determine the position coordinates of other pixels in the superimposed image through the image coordinate mark in the marked image, the resolution size and scaling ratio of the marked image, etc. The present disclosure does not limit the method for obtaining the scaling ratio of the marked image, which can be obtained through system data, etc.

[0085] Step 303: Overlay the multiple marker images onto the canvas image to determine an overlay image.

[0086] In some embodiments of the present disclosure, the terminal may superimpose a plurality of marker images on a canvas image to determine a superimposed image.

[0087] In some embodiments of the present disclosure, there is no limitation on the range of the canvas image occupied by the superimposed multiple marker images. They may completely overlap with the canvas image or only occupy part of the canvas image. For example, the superimposed multiple marker images only occupy the central area of ​​the canvas image.

[0088] In summary, according to the image processing method provided by the present disclosure, the method includes: determining a canvas image; determining the position of the marked image in the canvas image based on the image coordinate mark in the marked image; superimposing multiple marked images on the canvas image to determine the superimposed image, wherein the size of the superimposed image does not exceed the size of the canvas image. This solution determines the superimposed image by setting the output image canvas and the image coordinate mark in the marked image, so as to realize unified processing of multi-layer images by processing the superimposed image, thereby reducing hardware costs and device power consumption.

[0089] Figure 4 The following further shows a flowchart of an image processing method proposed in the present disclosure. Figure 3 The embodiment shown further explains step 303. Figure 4 The following steps may be included:

[0090] Step 401 : determining the overall transparency of a plurality of input images and the transparency of each pixel in the plurality of input images based on the transparency mark in the mark image.

[0091] In some embodiments of the present disclosure, the terminal may determine the overall transparency of multiple input images and the transparency of each pixel in the multiple input images based on the transparency mark in the mark image, thereby laying a foundation for determining the superimposed image.

[0092] In some embodiments of the present disclosure, for ease of adjustment, the input image may have a certain degree of transparency as a whole, and another degree of transparency in a local area. For example, if the input image size is 10×10, the overall transparency of the image is 12 (expressed in hexadecimal), and the transparency of the upper left 5×5 area of ​​the input image may be 4F.

[0093] Step 402: Determine the pixel value of each pixel in a plurality of input images.

[0094] In some embodiments of the present disclosure, the terminal may determine the pixel value of each pixel in a plurality of input images, laying a foundation for determining a superimposed image.

[0095] In some embodiments of the present disclosure, there is no limitation on the method for determining the pixel value of each pixel in an input image, which may be, for example, reading the pixel value of each pixel through an image processor.

[0096] Step 403 : determining the pixel value of each pixel of the superimposed image based on the overall transparency of the image, the transparency of each pixel and the pixel value of each pixel.

[0097] In some embodiments of the present disclosure, the terminal may determine the pixel value of each pixel of the superimposed image based on the overall transparency of the image, the transparency of each pixel, and the pixel value of each pixel to determine the superimposed image.

[0098] Specifically, the pixel value of each pixel of the superimposed image can be determined by the following formula:

[0099]

[0100] Among them, K represents any channel, P K Indicates the overall transparency of the image read in by channel K, A K i，j Indicates the transparency of the pixel at position (i, j) of the image read by channel K, R K i，j Indicates that channel K reads the pixel value of the image position coordinate (i, j); Mixer i，j It represents the pixel value of the pixel at the output image position coordinate (i, j), N represents the maximum number of channels, and N+1 represents the sum of the number of channels and the number of canvases.

[0101] Optionally, in some embodiments of the present disclosure, if channel K does not read an image, then P K , A K ij and R K ij All are 0; in some embodiments, there is no transparency component in the input image obtained by channel K, then A K i，j All are 1.

[0102] In summary, according to the image processing method provided by the present disclosure, the method includes: determining the overall transparency of multiple input images and the transparency of each pixel in the multiple input images based on the transparency mark in the marked image; determining the pixel value of each pixel in the multiple input images; determining the pixel value of each pixel of the superimposed image based on the overall transparency of the image, the transparency of each pixel and the pixel value of each pixel. The scheme of the present disclosure determines the pixel value of each pixel of the superimposed image by determining the transparency mark of the marked image and the pixel value of each pixel, thereby determining the superimposed image, so as to realize unified processing of multi-layer images by processing the superimposed image, thereby reducing hardware costs and device power consumption.

[0103] Figure 5 The following further shows a flowchart of an image processing method proposed in the present disclosure. Figure 1 The embodiment shown further explains step 104. Figure 5 The following steps may be included:

[0104] Step 501: determine one or more effect tag images based on the tag image.

[0105] In some embodiments of the present disclosure, the terminal may determine one or more effect marker images based on the marker image to perform image processing on the superimposed image.

[0106] In some embodiments of the present disclosure, the tagged image of each channel may include one or more image effect tags, and the terminal may output one or more effect tagged images based on each image effect tag, wherein each effect tagged image contains only one image effect tag.

[0107] Step 502: determining an output image based on the superimposed image and one or more effect mark images.

[0108] In some embodiments of the present disclosure, the terminal may determine an output image based on the overlay image and one or more effect mark images.

[0109] In some embodiments of the present disclosure, image effect processing may be performed on the superimposed image based on one or more effect tag images to determine an output image.

[0110] In summary, according to the image processing method provided by the present disclosure, the method includes: determining one or more effect marker images based on the marker image; and determining the output image based on the superimposed image and the one or more effect marker images. The scheme of the present disclosure performs image processing on the superimposed image by determining one or more effect marker images, thereby achieving unified processing of multi-layer images and reducing hardware costs and device power consumption.

[0111] Figure 6The following further shows a flowchart of an image processing method proposed in the present disclosure. Figure 5 The embodiment shown further explains step 501. Figure 6 The following steps may be included:

[0112] Step 601, determining the effect level value of the image enhancement level mark.

[0113] In some embodiments of the present disclosure, the terminal may determine the level value of the enhancement effect required for the pixel point by marking the image enhancement level mark in the image.

[0114] Step 602: determine the label value of each pixel in the first area of ​​the input image.

[0115] In some embodiments of the present disclosure, the terminal may determine the coordinate marking value of each pixel point in the first area of ​​the input image through the coordinate marking value.

[0116] In some embodiments of the present disclosure, the first area is a marked image area that needs to be processed for effect enhancement, wherein the first area can be the entire area of ​​the marked image or a partial area of ​​the marked image. The terminal can determine the size of the first area based on business requirements, and the present disclosure does not limit this.

[0117] Step 603: Determine the effect level mark value of each pixel of the effect mark image based on the effect level value and the mark value.

[0118] In some embodiments of the present disclosure, the terminal may determine the effect level marking value of each pixel of the effect marking image based on the effect level value and the marking value to determine one or more effect marking images.

[0119] Specifically, the effect level mark value of each pixel of the effect mark image can be determined by the following formula:

[0120]

[0121] Among them, level K Output image level value of any effect for channel K, ROI K ij is the label value of the pixel point at the canvas position coordinate (i, j) in the first area of ​​the channel K output image, Perf i,j The effect level value of the pixel point with coordinates (i, j) in any effect marking image, and the remaining parameters can be explained in Formula 4.1 and will not be repeated here.

[0122] For example, the effect level value of the pixel in the 100×100 position in the middle area of ​​the marked image is 2, and the effect level values ​​of the pixel in other positions are all 0, then 100×100 is ROI, that is, the first area, and 2 is the effect level value.

[0123] In summary, according to the image processing method provided by the present disclosure, the method includes: determining the effect level value of the image enhancement level mark; determining the mark value of each pixel in the first area of ​​the input image; and determining the effect level mark value of each pixel of the effect mark image based on the effect level value and the mark value. The scheme of the present disclosure determines the effect level mark value of each pixel of the effect mark image to determine one or more effect mark images, and uses the effect level images to perform image processing on the superimposed image to obtain an output image, thereby reducing hardware costs.

[0124] Figure 7 The following further shows a flowchart of an image processing method proposed in the present disclosure. Figure 5 The embodiment shown further explains step 502. Figure 7 The following steps may be included:

[0125] Step 701: Process the superimposed image using the first marked image among a plurality of effect marked images to determine a first processed image.

[0126] In some embodiments of the present disclosure, the terminal may process the superimposed image using a first marked image among a plurality of effect marked images to determine a first processed image.

[0127] In some embodiments of the present disclosure, the manner of processing the superimposed image is not limited, and for example, the superimposed image is processed in a raster scanning order.

[0128] like Figure 8 In the embodiment shown, effect mark image 0 is the first mark image, and effect mark image 0 is a brightness enhanced effect mark image. Effect mark image 0 can be used to perform effect 0 processing, i.e., brightness enhancement processing, on corresponding pixel points in the superimposed image to obtain a first processed image, i.e., a superimposed image processed by brightness enhancement.

[0129] Step 702: Use the second marked image among the plurality of effect marked images to process the first processed image until the plurality of marked images are traversed to obtain an output image.

[0130] In some embodiments of the present disclosure, the terminal may use the second marked image among the plurality of effect marked images to process the first processed image until the plurality of marked images are traversed to obtain an output image.

[0131] In some embodiments of the present disclosure, the second tagged image may be one or more tagged images. In other words, the second tagged image is all tagged images among all tagged images except the first tagged image.

[0132] like Figure 8 In the embodiment shown, the effect mark Figure 1 The effect mark image a is the second mark image, the effect mark Figure 1 is a contrast enhancement effect marker map, and effect marker map a is a color enhancement effect marker map. Figure 1 The first processed image is processed with effect 1, and the first processed image that has been processed with effect 1 is processed with effect a using effect label map a to obtain an output image.

[0133] In some embodiments of the present disclosure, the method for performing effect processing on the superimposed image may be to perform effect processing by means of hardware settings, for example, by setting a brightness lookup table, mapping pixels through the lookup table to determine the brightness enhancement level of each pixel; the method may be to perform effect processing by means of software settings, for example, generating a brightness enhancement curve through software, and the terminal may determine the brightness enhancement level of each pixel based on the brightness enhancement curve; or the method may be to perform effect processing by a combination of software and hardware, which is not limited by the present disclosure.

[0134] In summary, according to the image processing method provided by the present disclosure, the method includes: using the first marked image among multiple effect marked images to process the superimposed image to determine the first processed image; using the second marked image among multiple effect marked images to process the first processed image until traversing multiple marked images to obtain an output image. The scheme disclosed in the present disclosure processes the superimposed image by using the effect level image, realizes the use of a set of image processing engines to uniformly process multiple layers, and reduces hardware costs and device power consumption.

[0135] This solution marks multiple input images to determine the superimposed image and multiple marked images, so that a set of image processing engines can be used to uniformly process multi-layer images, reducing hardware costs and device power consumption. At the same time, by setting different enhancement effects and enhancement levels, the effect superposition of multiple layers can be adaptively completed, thereby improving image processing efficiency.

[0136] Therefore, this solution has the following beneficial effects:

[0137] 1. This solution marks multiple input images to determine the superimposed image and multiple marked images, so that a set of image processing engines can be used to uniformly process multi-layer images, reducing hardware costs and device power consumption.

[0138] 2. This solution can adaptively complete the effect superposition of multiple layers by setting different enhancement effects and enhancement levels, thereby improving image processing efficiency.

[0139] Fig. 9 The structure diagram of an image processing device 900 provided in an embodiment of the present disclosure includes:

[0140] An acquisition unit, used for acquiring an input image;

[0141] A first determining unit, configured to mark a plurality of input images to determine a plurality of marked images;

[0142] A second determining unit, configured to determine a superimposed image based on the plurality of marked images;

[0143] The third determining unit is used to determine an output image based on the superimposed image and the multiple marked images.

[0144] In summary, according to the image processing device proposed in the present disclosure, multiple input images of multiple channels are obtained; multiple input images are marked to determine multiple marked images; based on the multiple marked images, a superimposed image is determined; based on the superimposed image and the multiple marked images, an output image is determined. This solution marks multiple input images to determine the superimposed image and the multiple marked images, so that a set of image processing engines can be used to uniformly process multi-layer images, reducing hardware costs and device power consumption. At the same time, by setting different enhancement effects and enhancement levels, the effect superposition of multiple layers can be adaptively completed, thereby improving image processing efficiency.

[0145] In some embodiments of the present disclosure, the first determination unit 920 is also used to add one or more marks to each input image to determine a marked image of the input image, wherein the mark includes at least one of an image coordinate mark, an image enhancement effect mark, an image enhancement level mark, and a transparency mark.

[0146] In some embodiments of the present disclosure, the second determination unit 930 is also used to determine the canvas image; determine the position of the marked image in the canvas image based on the image coordinate mark in the marked image; and superimpose multiple marked images on the canvas image to determine the superimposed image, wherein the size of the superimposed image does not exceed the size of the canvas image.

[0147] In some embodiments of the present disclosure, the second determination unit 930 is also used to determine the overall transparency of multiple input images and the transparency of each pixel in the multiple input images based on the transparency mark in the marked image; determine the pixel value of each pixel in the multiple input images; and determine the pixel value of each pixel of the superimposed image based on the overall transparency of the image, the transparency of each pixel and the pixel value of each pixel.

[0148] In some embodiments of the present disclosure, the third determining unit 940 is further configured to determine one or more effect tagged images based on the tagged image; and determine an output image based on the superimposed image and the one or more effect tagged images.

[0149] In some embodiments of the present disclosure, the third determination unit 940 is also used to determine the effect level value of the image enhancement level mark; determine the mark value of each pixel point in the first area of ​​the input image; and determine the effect level mark value of each pixel point of the effect marked image based on the effect level value and the mark value.

[0150] In some embodiments of the present disclosure, the third determination unit 940 is also used to process the superimposed image using the first marked image among multiple effect marked images to determine the first processed image; and to process the first processed image using the second marked image among the multiple effect marked images until the multiple marked images are traversed to obtain the output image.

[0151] Since the device provided in the embodiment of the present disclosure corresponds to the methods provided in the above-mentioned embodiments, the implementation of the method is also applicable to the device provided in the embodiment and will not be described in detail in this embodiment.

[0152] In the embodiments provided in the present application, the methods and devices provided in the embodiments of the present application are introduced. In order to implement the functions in the methods provided in the embodiments of the present application, the electronic device may include a hardware structure and a software module, and implement the functions in the form of a hardware structure, a software module, or a hardware structure plus a software module. A function of the functions may be executed in the form of a hardware structure, a software module, or a hardware structure plus a software module.

[0153] Fig.10 1 is a block diagram of an electronic device 1000 for implementing the above-mentioned image processing method according to an exemplary embodiment. For example, the electronic device 1000 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0154] Reference Fig.10 , the electronic device 1000 may include one or more of the following components: a processing component 1002 , a memory 1004 , a power component 1006 , a multimedia component 1008 , an audio component 1010 , an input / output (I / O) interface 1012 , a sensor component 1014 , and a communication component 1016 .

[0155] The processing component 1002 generally controls the overall operation of the electronic device 1000, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 1002 may include one or more processors 1020 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 1002 may include one or more modules to facilitate the interaction between the processing component 1002 and other components. For example, the processing component 1002 may include a multimedia module to facilitate the interaction between the multimedia component 1008 and the processing component 1002.

[0156] The memory 1004 is configured to store various types of data to support operations on the electronic device 1000. Examples of such data include instructions for any application or method operating on the electronic device 1000, contact data, phone book data, messages, pictures, videos, etc. The memory 1004 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0157] The power supply component 1006 provides power to various components of the electronic device 1000. The power supply component 1006 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 1000.

[0158] The multimedia component 1008 includes a screen that provides an output interface between the electronic device 1000 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 1008 includes a front camera and / or a rear camera. When the electronic device 1000 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0159] The audio component 1010 is configured to output and / or input audio signals. For example, the audio component 1010 includes a microphone (MIC), and when the electronic device 1000 is in an operation mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 1004 or sent via the communication component 1016. In some embodiments, the audio component 1010 also includes a speaker for outputting audio signals.

[0160] I / O interface 1012 provides an interface between processing component 1002 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0161] The sensor assembly 1014 includes one or more sensors for providing various aspects of status assessment for the electronic device 1000. For example, the sensor assembly 1014 can detect the open / closed state of the electronic device 1000, the relative positioning of components, such as the display and keypad of the electronic device 1000, and the sensor assembly 1014 can also detect the position change of the electronic device 1000 or a component of the electronic device 1000, the presence or absence of user contact with the electronic device 1000, the orientation or acceleration / deceleration of the electronic device 1000, and the temperature change of the electronic device 1000. The sensor assembly 1014 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 1014 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 1014 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0162] The communication component 1016 is configured to facilitate wired or wireless communication between the electronic device 1000 and other devices. The electronic device 1000 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, 4G LTE, 5G NR (NewRadio) or a combination thereof. In an exemplary embodiment, the communication component 1016 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 1016 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0163] In an exemplary embodiment, the electronic device 1000 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0164] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 1004 including instructions, and the instructions can be executed by the processor 1020 of the electronic device 1000 to perform the above method for image processing. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0165] The embodiments of the present disclosure further provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the method described in the above embodiments of the present disclosure.

[0166] For electronic devices that may be chips or chip systems, see Fig.11 Schematic diagram of the chip structure shown. Fig.11 The chip shown includes a processor 1101 and an interface 1102. The number of the processor 1101 may be one or more, and the number of the interface 1102 may be multiple.

[0167] Optionally, the chip further includes a memory 1103, and the memory 1103 is used to store necessary computer programs and data.

[0168] Those skilled in the art may also understand that the various illustrative logical blocks and steps listed in the embodiments of the present application may be implemented by electronic hardware, computer software, or a combination of the two. Whether such functions are implemented by hardware or software depends on the specific application and the design requirements of the entire system. Those skilled in the art may use various methods to implement the functions for each specific application, but such implementation should not be understood as exceeding the scope of protection of the embodiments of the present application.

[0169] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0170] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0171] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0172] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (control method), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0173] It should be understood that the various parts of the embodiments of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0174] A person skilled in the art may understand that all or part of the steps in the above-mentioned embodiment method may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0175] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium. The above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0176] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. An image processing method, characterized in that: The method comprises: Get multiple input images with multiple channels; labeling the plurality of input images to determine a plurality of labeled images; determining a superimposed image based on the plurality of labeled images; Based on the overlay image and the plurality of marker images, an output image is determined.

2. The method according to claim 1, characterized in that: The marking the plurality of input images to determine a plurality of marked images comprises: For the input image, one or more tags are added to determine a tagged image of the input image, The mark includes at least one of an image coordinate mark, an image enhancement effect mark, an image enhancement level mark and a transparency mark.

3. The method according to claim 1, characterized in that The determining of the superimposed image based on the multiple marked images comprises: Determine the canvas image; Determining a position of the marked image in the canvas image based on an image coordinate mark in the marked image; The plurality of marker images are superimposed on the canvas image to determine the superimposed image, wherein a size of the superimposed image does not exceed a size of the canvas image.

4. The method according to claim 3, characterized in that The step of superimposing the plurality of marker images onto the canvas image to determine the superimposed image comprises: Determining the overall transparency of the plurality of input images and the transparency of each pixel in the plurality of input images based on the transparency mark in the mark image; Determine a pixel value of each pixel in the plurality of input images; Based on the overall transparency of the image, the transparency of each pixel and the pixel value of each pixel, the pixel value of each pixel of the superimposed image is determined.

5. The method according to claim 1, characterized in that The determining the output image based on the superimposed image and the plurality of marked images comprises: Based on the marker image, determining one or more effect marker images; Based on the overlay image and the one or more effect marker images, an output image is determined.

6. The method according to claim 5, characterized in that The determining one or more effect mark images based on the mark image comprises: Determine the effect level value of the image enhancement level mark; Determine a label value for each pixel in a first region of the input image; Based on the effect level value and the mark value, an effect level mark value of each pixel of the effect mark image is determined.

7. The method according to claim 5, characterized in that The determining of the output image based on the superimposed image and the one or more effect-marked images comprises: Using a first marked image among the plurality of effect marked images, the superimposed image is processed to determine a first processed image; The first processed image is processed by using a second marked image among the plurality of effect marked images until the plurality of marked images are traversed to obtain the output image.

8. An image processing device, characterized in that: The device comprises: An acquisition unit, used for acquiring an input image; A first determining unit, configured to mark a plurality of input images to determine a plurality of marked images; A second determining unit, configured to determine a superimposed image based on the plurality of marked images; The third determining unit is configured to determine an output image based on the superimposed image and the plurality of marked images.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

11. A chip, characterized in that: It comprises one or more interfaces and one or more processors; the interface is used to receive a signal from a memory of an electronic device and send the signal to the processor, the signal includes a computer instruction stored in the memory, and when the processor executes the computer instruction, the electronic device executes the method described in any one of claims 1 to 7.

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