WO2022027469A1 - 图像处理方法、装置和存储介质 - Google Patents

图像处理方法、装置和存储介质 Download PDF

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WO2022027469A1
WO2022027469A1 PCT/CN2020/107480 CN2020107480W WO2022027469A1 WO 2022027469 A1 WO2022027469 A1 WO 2022027469A1 CN 2020107480 W CN2020107480 W CN 2020107480W WO 2022027469 A1 WO2022027469 A1 WO 2022027469A1
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image
channel
full
resolution
fused
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PCT/CN2020/107480
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English (en)
French (fr)
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李伟冲
程祥
张玮
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深圳市汇顶科技股份有限公司
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Priority to PCT/CN2020/107480 priority Critical patent/WO2022027469A1/zh
Publication of WO2022027469A1 publication Critical patent/WO2022027469A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction

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  • the present application relates to the technical field of image processing, and in particular, to an image processing method, device and storage medium.
  • CFA color filter array
  • the technical solution of the present application provides an image processing method, device and storage medium, which can convert a WRGB CFA image into a full-resolution RGB image, can fuse the brightness information of the W channel and the chromaticity information of the RGB channel, and improve the dark light image quality below.
  • the technical solution of the present application provides an image processing method, including:
  • the full-resolution RGB image and the full-resolution W channel image are combined to obtain a combined RGB image.
  • the process of combining the full-resolution RGB image and the full-resolution W channel image to obtain the combined RGB image includes:
  • the to-be-fused image and the full-resolution W channel image are fused to obtain a fused image
  • the process of combining the full-resolution RGB image and the full-resolution W channel image to obtain the combined RGB image includes:
  • the color-restored image is used as the image to be fused, and the image to be fused and the full-resolution W-channel image are fused.
  • the process of converting the WRGB CFA image into a Bayer image includes:
  • the restored Bayer image is obtained.
  • the residual is Among them, MG is a binary image, the G channel position data value of the binary image is 1, the data value of other positions is 0, and G sub is the G channel sampling image, is the initial estimated value of the G channel.
  • the process of fusing the to-be-fused image and the full-resolution W-channel image includes:
  • the color restoration includes one or any combination of the following:
  • an image processing device including:
  • the image acquisition module is used to acquire the WRGB color filter array CFA image
  • a conversion module for converting the WRGB CFA image into a Bayer image and converting the Bayer image into a full-resolution RGB image
  • the combining module is used for combining the full-resolution RGB image and the full-resolution W channel image to obtain a combined RGB image.
  • an image processing device including:
  • a processor and a memory wherein the memory is used to store at least one instruction, and the instruction is loaded and executed by the processor to implement the above-mentioned image processing method.
  • the technical solution of the present application provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when it runs on a computer, the computer executes the above-mentioned image processing method.
  • the image processing method, device, and storage medium in the embodiments of the present application generate a Bayer image based on a WRGB CFA image, convert the Bayer image into a full-resolution RGB image, and generate a full-resolution W-channel image based on the WRGB CFA image, and finally Combining the RGB image and the W channel image to obtain the combined RGB image, the WRGB CFA image can be converted into a full-resolution RGB image, and the luminance information of the W channel and the chromaticity information of the RGB channel are integrated, which improves the performance in dark light. image quality.
  • FIG. 1 is a schematic flowchart of an image processing method in an embodiment of the present application.
  • FIG. 2 is a schematic diagram of a process architecture corresponding to FIG. 1;
  • FIG. 3 is a schematic diagram of the pixel arrangement of the WRGB CFA image in the embodiment of the application.
  • FIG. 4 is a schematic flowchart of another image processing method in an embodiment of the present application.
  • FIG. 5 is a schematic diagram of a process architecture corresponding to FIG. 4;
  • FIG. 6 is a schematic flowchart of another image processing method in an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a process structure corresponding to FIG. 6;
  • FIG. 8 is a schematic flowchart of a part of an image processing method in an embodiment of the present application.
  • FIG. 9 is a schematic diagram of a process structure corresponding to FIG. 8.
  • FIG. 10 is a schematic diagram of a process structure of interpolating the W channel at the R channel position in an embodiment of the present application
  • FIG. 11 is a simplified schematic diagram of a process structure for interpolating the W channel at the B channel position according to an embodiment of the present application
  • FIG. 12 is a simplified schematic diagram of a process structure for interpolating the W channel at the G channel position according to an embodiment of the present application
  • FIG. 13 is a schematic flowchart of another part of an image processing method in an embodiment of the present application.
  • Fig. 15 is the final image obtained after the WRGB CFA image corresponding to Fig. 14 is converted by the method shown in Fig. 4;
  • Figure 16 is the final image obtained after the WRGB CFA image corresponding to Figure 14 is converted by the method shown in Figure 6;
  • FIG. 17 is a structural block diagram of an image processing apparatus in an embodiment of the present application.
  • FIG. 1 is a schematic flowchart of an image processing method in an embodiment of the application
  • FIG. 2 is a schematic diagram of a flowchart corresponding to FIG. 1
  • FIG. 3 is a WRGB CFA in an embodiment of the application.
  • a schematic diagram of image pixel arrangement, an embodiment of the present application provides an image processing method, including:
  • Step 101 obtaining a WRGB color filter array CFA image
  • the WRGB CFA image in step 101 is the original image output by the image sensor.
  • W represents the white channel
  • R represents the red channel
  • G represents the green channel
  • B represents the blue channel.
  • Step 102 convert the WRGB CFA image into a Bayer image, and convert the Bayer image into a full-resolution RGB image;
  • a pixel in the Bayer image has only one color, red or green or blue, so each pixel can have three colors of red, green, and blue through interpolation, that is, restore the Bayer image to full-resolution RGB image.
  • Step 103 Interpolate W channel data in the R channel position, G channel position and B channel position in the WRGB CFA image to generate a full resolution W channel image;
  • Step 104 Combine the full-resolution RGB image and the full-resolution W-channel image to obtain a combined RGB image.
  • the full-resolution RGB image generated in step 102 is used to provide RGB chrominance information in the WRGB CFA image
  • the full-resolution W channel image is used to provide the WRGB CFA image in the luminance information of the W channel.
  • the image processing method in this embodiment of the present application generates a Bayer image based on a WRGB CFA image, converts the Bayer image into a full-resolution RGB image, and generates a full-resolution W-channel image based on the WRGB CFA image, and finally converts the RGB image and W
  • the channel images are combined to obtain a combined RGB image, which can convert the WRGB CFA image into a full-resolution RGB image, which combines the luminance information of the W channel and the chromaticity information of the RGB channel, which improves the image quality in dark light.
  • FIG. 4 is a schematic flowchart of another image processing method in this embodiment of the present application
  • FIG. 5 is a schematic flowchart of the flowchart corresponding to FIG. 4 .
  • the RGB image and the full-resolution W channel image are combined, and the process of obtaining the combined RGB image includes:
  • Step 1041 taking the full-resolution RGB image as the image to be fused, and merging the to-be-fused image and the full-resolution W channel image to obtain a fused image;
  • Step 1042 Perform color restoration on the fused image to obtain an image with enhanced brightness.
  • the image obtained by this method has more details, which is more conducive to color restoration.
  • FIG. 6 is a schematic flowchart of another image processing method in an embodiment of the present application
  • FIG. 7 is a schematic flowchart of the flowchart corresponding to FIG. 6 .
  • the RGB image of the resolution is combined with the full-resolution W channel image, and the process of obtaining the combined RGB image includes:
  • Step 1043 performing color restoration on the full-resolution RGB image to obtain an image after color restoration
  • Step 1044 Use the image after color restoration as the image to be fused, and fuse the image to be fused with the full-resolution W-channel image to obtain a fused image.
  • the implementation of this scheme is more flexible and more compatible, and is suitable for Existing Image Signal Processor (ISP).
  • ISP Existing Image Signal Processor
  • FIG. 8 is a schematic flowchart of a part of an image processing method in an embodiment of the present application
  • FIG. 9 is a schematic flowchart of a flowchart corresponding to FIG. 8
  • the WRGB CFA image is The process of converting to a Bayer image includes:
  • Step 1021 obtain the W-channel sampling map of the WRGB CFA image at the W-channel position, and obtain the G-channel sampling map of the WRGB CFA image at the G-channel position;
  • Step 1022 Interpolate the W channel at the G channel position for the W channel sampling map to obtain the W interpolation map
  • Step 1023 using the W interpolation map as the guide map, conduct guided filtering Guided Filter processing on the G channel sampling map to obtain the initial estimated value of the G channel;
  • Step 1024 generating residuals according to the G channel sampling map
  • Step 1025 Interpolate the residual at the W channel position to obtain the interpolated residual, and add the interpolated residual to the initial estimated value of the G channel to obtain the G channel interpolation map;
  • Step 1026 Obtain a converted Bayer image according to the G channel interpolation map and the R channel and B channel in the WRGB CFA image.
  • the residual is Among them, M G is a binary image, the G channel position data value of the binary image is 1, the data value of other positions is 0, G sub is the G channel sampling image, is the initial estimated value of the G channel.
  • the way of generating a full-resolution W-channel image through interpolation can be similar to the above-mentioned process of converting a WRGB CFA image into a Bayer image. For example, as shown in FIG. 10, FIG.
  • a schematic diagram of the process structure of interpolating the W channel at the R channel position first obtain the W channel sampling map of the WRGB CFA image at the W channel position, and obtain the R channel sampling map of the WRGB CFA image at the R channel position;
  • the R channel sampling map interpolates the R channel at the W channel position to obtain the R interpolation map; using the R interpolation map as the guide map, conduct guided filtering processing on the W channel sampling map to obtain the initial estimated value of the W channel; generate the residual according to the W channel sampling map,
  • the residual is Among them, M W is a binary image, the data value of the W channel position of the binary image is 1, the data value of other positions is 0, and W sub is the W channel sampling image, is the initial estimated value of the W channel; interpolate the residual at the position of the R channel to obtain the interpolated residual, and add the interpolated residual to the initial estimated value of the W channel to obtain the W channel interpolation map, that is, based on the R
  • FIG. 10 A simplified schematic diagram of the process architecture of interpolating the W channel at the position of the G channel.
  • the corresponding W channel interpolation map can be obtained based on the B channel sampling map by a similar method, and the corresponding W channel interpolation map can be obtained based on the G channel sampling map.
  • the three W-channel interpolation maps in Figure 11 and Figure 12 can obtain full-resolution W-channel images.
  • FIG. 13 is a schematic flowchart of another part of an image processing method in the embodiment of the present application.
  • the image to be fused and the full-resolution W-channel image are The process of fusion includes:
  • Step 201 converting the image to be fused from the RGB color space to the YCbCr color space, to obtain the converted image to be fused;
  • Step 202 taking the Y component in the converted image to be fused as a guide map, performing guide filtering processing on the full-resolution W-channel image to obtain the W-channel initial estimated value;
  • step 202 the process of conducting guided filtering processing on the full-resolution W-channel image can be expressed by the following formula:
  • i,j represent the pixel coordinates
  • q, p represent the height and width of the filtering window, respectively
  • a p, q and b p, q both represent constant coefficients in the filtering window determined by q, p, Y i, j represent the The pixel value of the Y component in the fused image at position i, j, w p, q represents the filter window
  • White i, j represents the pixel value of the full-resolution W channel image at position i, j.
  • Step 203 replacing the Y component in the converted image to be fused with the initial estimated value of the W channel to obtain the replaced image to be fused;
  • Step 204 Convert the replaced image to be fused from the YCbCr color space to the RGB color space.
  • the color restoration in the above step 1042 or 1043 includes one or any combination of the following: automatic white balance (Automatic white balance, AWB), color correction matrix (Color Correction Matrix, CCM) processing, gamma correction and Tone Curve adjustment.
  • automatic white balance Auto white balance, AWB
  • color correction matrix Color Correction Matrix, CCM
  • FIG. 14 is an example of a WRGB CFA image in the embodiment of the application
  • FIG. 15 is the WRGB CFA image corresponding to FIG. 14 after being converted by the method shown in FIG. 4
  • the obtained final image Fig. 16 is the final image obtained after the WRGB CFA image corresponding to Fig. 14 is converted by the method shown in Fig. 6, according to the comparison of Fig. 14, Fig. 15 and Fig. 16, it can be seen that shown in Fig. 4
  • the image quality obtained by performing fusion first and then performing color restoration is higher.
  • FIG. 17 is a structural block diagram of an image processing apparatus in an embodiment of the present application.
  • An embodiment of the present application further provides an image processing apparatus, including: an image acquisition module 1 for acquiring a WRGB color filter array CFA Image; conversion module 2 for converting WRGB CFA images to Bayer images and Bayer images to full-resolution RGB images; processing module 3 for R channel position, G channel position and Interpolate the W-channel data in the B-channel position to generate a full-resolution W-channel image; the combining module 4 is used to combine the full-resolution RGB image and the full-resolution W-channel image to obtain a combined RGB image.
  • the image processing apparatus may apply the above-mentioned image processing method, and the specific process and principle will not be repeated.
  • the combination module 4 is specifically used to use the full-resolution RGB image as the image to be fused, and fuse the to-be-fused image and the full-resolution W channel image to obtain a fused image; Color restoration.
  • the combination module 4 is specifically used to perform color restoration on a full-resolution RGB image to obtain a color-restored image; use the color-restored image as an image to be fused, and make the image to be fused and the full-resolution W image to be fused.
  • the channel images are fused.
  • the conversion module 2 obtain the W-channel sampling map of the WRGB CFA image at the W-channel position, and obtain the G-channel sampling map of the WRGB CFA image at the G-channel position;
  • the W channel sampling map interpolates the W channel at the G channel position to obtain the W interpolation map; using the W interpolation map as the oriented map, the G channel sampling map is guided and filtered to obtain the initial estimated value of the G channel; the residual is generated according to the G channel sampling map; Interpolate the residual at the W channel position to obtain the interpolated residual, and add the interpolated residual to the initial estimated value of the G channel to obtain the G channel interpolation map; according to the G channel interpolation map and the R in the WRGB CFA image channel and B channel to obtain the restored Bayer image.
  • the residual is: Among them, M G is a binary image, the G channel position data value of the binary image is 1, the data value of other positions is 0, G sub is the G channel sampling image, is the initial estimated value of the G channel.
  • the process of combining the image to be fused with the full-resolution W channel image in combination with module 4 includes: converting the image to be fused from the RGB color space to the YCbCr color space, and obtaining the converted image to be fused;
  • the Y component in the image to be fused is the guide map, and the full-resolution W channel image is subjected to guided filtering to obtain the initial estimated value of the W channel; the Y component in the converted image to be fused is replaced by the initial estimated value of the W channel.
  • obtain the replaced image to be fused convert the replaced image to be fused from the YCbCr color space to the RGB color space.
  • color restoration includes one or any combination of: automatic white balance, color correction matrix processing, gamma correction, and tone curve adjustment.
  • each module of the image processing apparatus is only a division of logical functions, and may be fully or partially integrated into one physical entity in actual implementation, or may be physically separated.
  • these modules can all be implemented in the form of software calling through processing elements; they can also all be implemented in hardware; some modules can also be implemented in the form of software calling through processing elements, and some modules can be implemented in hardware.
  • the image acquisition module 1 can be a separately established processing element, or can be integrated in an image processing device, such as a certain chip of the image processing device, and can also be stored in the memory of the image processing device in the form of a program, The functions of the above modules are called and executed by a certain processing element of the image processing apparatus.
  • the implementation of other modules is similar.
  • each step of the above-mentioned method or each of the above-mentioned modules can be completed by an integrated logic circuit of hardware in the processor element or an instruction in the form of software.
  • the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuit (ASIC), or one or more microprocessors (digital) singnal processor, DSP), or, one or more field programmable gate arrays (Field Programmable Gate Array, FPGA), etc.
  • ASIC Application Specific Integrated Circuit
  • DSP digital signal processor
  • FPGA Field Programmable Gate Array
  • the processing element may be a general-purpose processor, such as a central processing unit (Central Processing Unit, CPU) or other processors that can invoke programs.
  • these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).
  • SOC system-on-a-chip
  • an embodiment of the present application further provides an image processing apparatus, including: a processor and a memory, where the memory is used to store at least one instruction, and the instruction is loaded and executed by the processor to implement the above image processing method.
  • the image processing apparatus may apply the above-mentioned image processing method, and the specific process and principle will not be repeated.
  • the number of processors may be one or more, and the processors and the memory may be connected by a bus or in other ways.
  • the memory can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions/modules corresponding to the image detection method in the embodiments of the present application.
  • the processor executes various functional applications and data processing by running the non-transitory software programs, instructions and modules stored in the memory, that is, to implement the method in any of the above method embodiments.
  • the memory may include a stored program area and a stored data area, wherein the stored program area may store an operating system, an application program required for at least one function; and necessary data and the like. Additionally, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device.
  • Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when it runs on a computer, it causes the computer to execute the image processing method of the foregoing embodiments.
  • the above-mentioned embodiments it may be implemented in whole or in part by software, hardware, firmware or any combination thereof.
  • software it can be implemented in whole or in part in the form of a computer program product.
  • the computer program product includes one or more computer instructions.
  • the computer program instructions when loaded and executed on a computer, result in whole or in part of the processes or functions described herein.
  • the computer may be a general purpose computer, special purpose computer, computer network, or other programmable device.
  • the computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be downloaded from a website site, computer, server, or data center Transmission to another website site, computer, server, or data center by wire (eg, coaxial cable, optical fiber, digital subscriber line) or wireless (eg, infrared, wireless, microwave, etc.).
  • the computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, a data center, or the like that includes an integration of one or more available media.
  • the usable media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, DVD), or semiconductor media (eg, Solid State Disk), and the like.
  • “at least one” refers to one or more, and “multiple” refers to two or more.
  • “And/or”, which describes the association relationship of the associated objects, indicates that there can be three kinds of relationships, for example, A and/or B, which can indicate the existence of A alone, the existence of A and B at the same time, and the existence of B alone. where A and B can be singular or plural.
  • the character “/” generally indicates that the associated objects are an “or” relationship.
  • “At least one of the following” and similar expressions refer to any combination of these items, including any combination of single or plural items.
  • At least one of a, b, and c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, c may be single or multiple.

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Abstract

一种图像处理方法、装置和存储介质，涉及图像处理技术领域，能够将WRGB CFA图像转换为全分辨率的RGB图像，融合W通道的亮度信息和RGB通道的色度信息，提高了暗光下的图像质量。该图像处理方法包括：获取WRGB色彩滤波阵列CFA图像（101）；将WRGB CFA图像转换为拜耳Bayer图像；将Bayer图像转换为全分辨率的RGB图像（102）；在WRGB CFA图像中的R通道位置、G通道位置和B通道位置中插值W通道数据，生成全分辨率的W通道图像（103）；将全分辨率的RGB图像和全分辨率的W通道图像进行结合，得到结合后的RGB图像（104）。

Description

图像处理方法、装置和存储介质 技术领域
本申请涉及图像处理技术领域，特别涉及一种图像处理方法、装置和存储介质。
背景技术
目前，大部分成像设备使用彩色滤光片阵列(Color filter array，CFA)，目前的CFA包括WRGB CFA，其中，通过WRGB CFA进行成像具有灵敏度高的优点，但是由于空间分辨率较低，因此难以将WRGB CFA图像处理成RGB图像。
发明内容
本申请技术方案提供了一种图像处理方法、装置和存储介质，能够将WRGB CFA图像转换为全分辨率的RGB图像，可以融合W通道的亮度信息和RGB通道的色度信息，提高了暗光下的图像质量。
第一方面，本申请技术方案提供了一种图像处理方法，包括：
获取WRGB色彩滤波阵列CFA图像；
将所述WRGB CFA图像转换为拜耳Bayer图像；
将所述Bayer图像转换为全分辨率的RGB图像；
在所述WRGB CFA图像中的R通道位置、G通道位置和B通道位置中插值W通道数据，生成全分辨率的W通道图像；
将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像。
可选地，所述将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像的过程包括：
将所述全分辨率的RGB图像作为待融合图像，使所述待融合图像和所述全分辨率的W通道图像进行融合，得到融合后的图像；
对所述融合后的图像进行颜色还原。
可选地，所述将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像的过程包括：
对所述全分辨率的RGB图像进行颜色还原，得到颜色还原后的图像；
将所述颜色还原后的图像作为待融合图像，使所述待融合图像和所述全分辨率的W通道图像进行融合。
可选地，所述将所述WRGB CFA图像转换为拜耳Bayer图像的过程包括：
获取所述WRGB CFA图像在W通道位置的W通道采样图，以及获取WRGB CFA图像在G通道位置的G通道采样图；
对所述W通道采样图在G通道位置插值W通道得到W插值图；
以所述W插值图为导向图，对所述G通道采样图进行导向滤波处理，得到G通道初始估计值；
根据所述G通道采样图生成残差；
将所述残差在W通道位置进行插值，得到插值后的残差，将所述插值后的残差与所述G通道初始估计值相加，得到G通道插值图；
根据所述G通道插值图和所述WRGB CFA图像中的R通道及B通道，得到还原后的所述Bayer图像。
可选地，所述残差为
Figure PCTCN2020107480-appb-000001
其中，M G为二值图，二值图的G通道位置数据值为1，其他位置的数据值为0，G sub为所述G通道采样图，
Figure PCTCN2020107480-appb-000002
为所述G通道初始估计值。
可选地，所述使所述待融合图像和所述全分辨率的W通道图像进行融合的过程包括：
将所述待融合图像从RGB色彩空间转换为YCbCr色彩空间，得到转换后的待融合图像；
以所述转换后的待融合图像中的Y分量为导向图，对所述全分辨率的W通道图像进行导向滤波处理，得到W通道初始估计值；
将所述转换后的待融合图像中的Y分量替换为所述W通道初始估计值，得到替换后的待融合图像；
将所述替换后的待融合图像从YCbCr色彩空间转换为RGB色彩空间。
可选地，所述颜色还原包括以下各项之一或任意组合：
自动白平衡、色彩校正矩阵处理、伽玛校正和色调曲线调节。
第二方面，本申请技术方案提供了一种图像处理装置，包括：
图像获取模块，用于获取WRGB色彩滤波阵列CFA图像；
转换模块，用于将所述WRGB CFA图像转换为拜耳Bayer图像以及将所述Bayer图像转换为全分辨率的RGB图像；
处理模块，用于在所述WRGB CFA图像中的R通道位置、G通道位置和B通道位置中插值W通道数据，生成全分辨率的W通道图像；
结合模块，用于将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像。
第三方面，本申请技术方案提供了一种图像处理装置，包括：
处理器和存储器，所述存储器用于存储至少一条指令，所述指令由所述处理器加载并执行时以实现上述的图像处理方法。
第四方面，本申请技术方案提供了一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机程序，当其在计算机上运行时，使得计算机执行上述的图像处理方法。
本申请实施例中的图像处理方法、装置和存储介质，基于WRGB CFA图像生成Bayer图像，将Bayer图像转换为全分辨率的RGB图像，以及基于WRGB CFA图像生成全分辨率的W通道图像，最后将RGB图像和W通道图像结合，得到结合后的RGB图像，能够将WRGB CFA图像转换为全分辨率的RGB图像，融合了W通道的亮度信息和RGB通道的色度信息，提高了暗光下的图像质量。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本申请实施例中一种图像处理方法的流程示意图；
图2为图1对应的流程架构示意图；
图3为本申请实施例中WRGB CFA图像像素排布示意图；
图4为本申请实施例中另一种图像处理方法的流程示意图；
图5为图4对应的流程架构示意图；
图6为本申请实施例中另一种图像处理方法的流程示意图；
图7为图6对应的流程架构示意图；
图8为本申请实施例中一种图像处理方法的一部分流程示意图；
图9为图8对应的流程架构示意图；
图10为本申请实施例中一种在R通道位置处插值W通道的流程架构示意图；
图11为本申请实施例中一种在B通道位置处插值W通道的流程架构简化示意图；
图12为本申请实施例中一种在G通道位置处插值W通道的流程架构简化示意图；
图13为本申请实施例中一种图像处理方法的另一部分流程示意图；
图14为本申请实施例中一种WRGB CFA图像的示例；
图15为图14对应的WRGB CFA图像在经过图4所示的方法转换后得到的最终图像；
图16为图14对应的WRGB CFA图像在经过图6所示的方法转换后得到的最终图像；
图17为本申请实施例中一种图像处理装置的结构框图。
具体实施方式
本申请的实施方式部分使用的术语仅用于对本申请的具体实施例进行解释，而非旨在限定本申请。
如图1、图2和图3所示，图1为本申请实施例中一种图像处理方法的流程示意图，图2为图1对应的流程架构示意图，图3为本申请实施例中WRGB CFA图像像素排布示意图，本申请实施例提供了一种图像处理方法，包括：
步骤101、获取WRGB色彩滤波阵列CFA图像；
其中，步骤101中的WRGB CFA图像为图像传感器输出的原始图像，在WRGB CFA图像中，W表示白色通道，R表示红色通道，G表示绿色通道，B表示蓝色通道。
步骤102、将WRGB CFA图像转换为拜耳Bayer图像，将Bayer图像转换为全分辨率的RGB图像；
其中，Bayer图像中一个像素点只有一个颜色，红色或绿色或蓝色，因此可以通过插值的方式使每个像素点具有红、绿、蓝三种颜色，即将Bayer图像还原为了全分辨率的RGB图像。
步骤103、在WRGB CFA图像中的R通道位置、G通道位置和B通道位置中插值W通道数据，生成全分辨率的W通道图像；
步骤104、将全分辨率的RGB图像和全分辨率的W通道图像进行结合，得到结合后的RGB图像。
其中，步骤102中生成的全分辨率的RGB图像用于提供WRGB CFA图像中RGB的色度信息，全分辨率的W通道图像用于提供WRGB CFA图像中W通道的亮度信息。
本申请实施例中的图像处理方法，基于WRGB CFA图像生成Bayer图像，将Bayer图像转换为全分辨率的RGB图像，以及基于WRGB CFA图像生成全分辨率的W通道图像，最后将RGB图像和W通道图像结合，得到结合后的RGB图像，能够将WRGB CFA图像转换为全分辨率的RGB图像，融合了W通道的亮度信息和RGB 通道的色度信息，提高了暗光下的图像质量。
可选地，如图4和图5所示，图4为本申请实施例中另一种图像处理方法的流程示意图，图5为图4对应的流程架构示意图，上述步骤104、将全分辨率的RGB图像和全分辨率的W通道图像进行结合，得到结合后的RGB图像的过程包括：
步骤1041、将全分辨率的RGB图像作为待融合图像，使待融合图像和全分辨率的W通道图像进行融合，得到融合后的图像；
步骤1042、对融合后的图像进行颜色还原，得到亮度增强后的图像，该方法得到的图像具有更多的细节，更有利于颜色的还原。
可选地，如图6和图7所示，图6为本申请实施例中另一种图像处理方法的流程示意图，图7为图6对应的流程架构示意图，上述步骤104、将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像的过程包括：
步骤1043、对全分辨率的RGB图像进行颜色还原，得到颜色还原后的图像；
步骤1044、将颜色还原后的图像作为待融合图像，使待融合图像和全分辨率的W通道图像进行融合，得到融合后的图像，该方案的实现方式更加灵活，兼容性更高，适用于现有的图像信号处理器(Image Signal Processor，ISP)。
可选地，如图8和图9所示，图8为本申请实施例中一种图像处理方法的一部分流程示意图，图9为图8对应的流程架构示意图，上述步骤102中将WRGB CFA图像转换为拜耳Bayer图像的过程包括：
步骤1021、获取WRGB CFA图像在W通道位置的W通道采样图，以及获取WRGB CFA图像在G通道位置的G通道采样图；
步骤1022、对W通道采样图在G通道位置插值W通道得到W插值图；
步骤1023、以W插值图为导向图，对G通道采样图进行导向滤波Guided Filter处理，得到G通道初始估计值；
步骤1024、根据G通道采样图生成残差；
步骤1025、将残差在W通道位置进行插值，得到插值后的残差，将插值后的残差与G通道初始估计值相加，得到G通道插值图；
步骤1026、根据G通道插值图和WRGB CFA图像中的R通道及B通道，得到转换后的Bayer图像。
可选地，残差为
Figure PCTCN2020107480-appb-000003
其中，M G为二值图，二值图的G通道位置数据值为1，其他位置的数据值为0，G sub为G通道采样图，
Figure PCTCN2020107480-appb-000004
为G通道初始估计值。
另外，在上述步骤103中，通过插值的方式生成全分辨率的W通道图像的方式可以与上述将WRGB CFA图像转换为拜耳Bayer图像的过程类似，例如，如图10所示，图10为本申请实施例中一种在R通道位置处插值W通道的流程架构示意图，首先获取WRGB CFA图像在W通道位置的W通道采样图，以及获取WRGB CFA图像在R通道位置的R通道采样图；对R通道采样图在W通道位置插值R通道得到R插值图；以R插值图为导向图，对W通道采样图进行导向滤波处理，得到W通道初始估计值；根据W通道采样图生成残差，例如，残差为
Figure PCTCN2020107480-appb-000005
其中，M W为二值图，二值图的W通道位置数据值为1，其他位置的数据值为0，W sub为W通道采样图，
Figure PCTCN2020107480-appb-000006
为W通道初始估计值；将残差在R通道位置进行插值，得到插值后的残差，将插值后的残差与W通道初始估计值相加，得到W通道插值图，即基于R通道采样图得到对应的W通道插值图；如图11和图12所示，图11为本申请实施例中一种在B通道位置处插值W通道的流程架构简化示意图，图12为本申请实施例中一种在G通道位置处插值W通道的流程架构简化示意图，可以通过类似的方法基于B通道采样图得到对应的W通道插值图，基于G通道采样图得到对应的W通道插值图，根据图10、图11和图12中的三个W通道插值图可以得到全分辨率的W通道图像。
可选地，如图13所示，图13为本申请实施例中一种图像处理方法的另一部分流程示意图，在上述步骤1041或步骤1044中，使 待融合图像和全分辨率的W通道图像进行融合的过程包括：
步骤201、将待融合图像从RGB色彩空间转换为YCbCr色彩空间，得到转换后的待融合图像；
步骤202、以转换后的待融合图像中的Y分量为导向图，对全分辨率的W通道图像进行导向滤波处理，得到W通道初始估计值；
其中，在步骤202中对全分辨率的W通道图像进行导向滤波处理的过程可以用以下公式表示：
Figure PCTCN2020107480-appb-000007
Figure PCTCN2020107480-appb-000008
Figure PCTCN2020107480-appb-000009
其中，i,j表示像素坐标，
Figure PCTCN2020107480-appb-000010
表示W通道初始估计值，q,p分别表示滤波窗口的高和宽，a p,q和b p,q均表示在q,p确定的滤波窗口内的常量系数，Y i,j表示对于待融合图像中的Y分量在i,j位置的像素值，w p,q表示滤波窗口，White i,j表示全分辨率的W通道图像在i,j位置的像素值。
步骤203、将转换后的待融合图像中的Y分量替换为W通道初始估计值，得到替换后的待融合图像；
步骤204、将替换后的待融合图像从YCbCr色彩空间转换为RGB色彩空间。
可选地，上述步骤1042或1043中的颜色还原包括以下各项之一或任意组合：自动白平衡(Automatic white balance，AWB)、色彩校正矩阵(Color Correction Matrix，CCM)处理、伽玛Gamma校正和色调曲线Tone Curve调节。
另外，如图14、图15和图16所示，图14为本申请实施例中一种WRGB CFA图像的示例，图15为图14对应的WRGB CFA图像在经过图4所示的方法转换后得到的最终图像，图16为图14对应的WRGB CFA图像在经过图6所示的方法转换后得到的最终图 像，根据图14、图15和图16的对比可以看出，在图4所示的方法中先进行融合后进行颜色还原所得到的图像质量更高。
如图17所示，图17为本申请实施例中一种图像处理装置的结构框图，本申请实施例还提供一种图像处理装置，包括：图像获取模块1，用于获取WRGB色彩滤波阵列CFA图像；转换模块2，用于将WRGB CFA图像转换为拜耳Bayer图像以及将Bayer图像转换为全分辨率的RGB图像；处理模块3，用于在WRGB CFA图像中的R通道位置、G通道位置和B通道位置中插值W通道数据，生成全分辨率的W通道图像；结合模块4，用于将全分辨率的RGB图像和全分辨率的W通道图像进行结合，得到结合后的RGB图像。该图像处理装置可以应用上述的图像处理方法，具体过程和原理不再赘述。
可选地，结合模块4具体用于，将全分辨率的RGB图像作为待融合图像，使待融合图像和全分辨率的W通道图像进行融合，得到融合后的图像；对融合后的图像进行颜色还原。
可选地，结合模块4具体用于，对全分辨率的RGB图像进行颜色还原，得到颜色还原后的图像；将颜色还原后的图像作为待融合图像，使待融合图像和全分辨率的W通道图像进行融合。
可选地，转换模块2将WRGB CFA图像转换为拜耳Bayer图像的过程中：获取WRGB CFA图像在W通道位置的W通道采样图，以及获取WRGB CFA图像在G通道位置的G通道采样图；对W通道采样图在G通道位置插值W通道得到W插值图；以W插值图为导向图，对G通道采样图进行导向滤波处理，得到G通道初始估计值；根据G通道采样图生成残差；将残差在W通道位置进行插值，得到插值后的残差，将插值后的残差与G通道初始估计值相加，得到G通道插值图；根据G通道插值图和WRGB CFA图像中的R通道及B通道，得到还原后的Bayer图像。
可选地，转换模块2根据G通道采样图生成残差的过程中，残差为
Figure PCTCN2020107480-appb-000011
其中，M G为二值图，二值图的G通道位置数据值为1，其他位置的数据值为0，G sub为G通道采样图，
Figure PCTCN2020107480-appb-000012
为G 通道初始估计值。
可选地，结合模块4使待融合图像和全分辨率的W通道图像进行融合的过程包括：将待融合图像从RGB色彩空间转换为YCbCr色彩空间，得到转换后的待融合图像；以转换后的待融合图像中的Y分量为导向图，对全分辨率的W通道图像进行导向滤波处理，得到W通道初始估计值；将转换后的待融合图像中的Y分量替换为W通道初始估计值，得到替换后的待融合图像；将替换后的待融合图像从YCbCr色彩空间转换为RGB色彩空间。
可选地，颜色还原包括以下各项之一或任意组合：自动白平衡、色彩校正矩阵处理、伽玛校正和色调曲线调节。
应理解以上图像处理装置的各个模块的划分仅仅是一种逻辑功能的划分，实际实现时可以全部或部分集成到一个物理实体上，也可以物理上分开。且这些模块可以全部以软件通过处理元件调用的形式实现；也可以全部以硬件的形式实现；还可以部分模块以软件通过处理元件调用的形式实现，部分模块通过硬件的形式实现。例如，图像获取模块1可以为单独设立的处理元件，也可以集成在图像处理装置，例如图像处理装置的某一个芯片中实现，此外，也可以以程序的形式存储于图像处理装置的存储器中，由图像处理装置的某一个处理元件调用并执行以上各个模块的功能。其它模块的实现与之类似。此外这些模块全部或部分可以集成在一起，也可以独立实现。这里所述的处理元件可以是一种集成电路，具有信号的处理能力。在实现过程中，上述方法的各步骤或以上各个模块可以通过处理器元件中的硬件的集成逻辑电路或者软件形式的指令完成。
例如，以上这些模块可以是被配置成实施以上方法的一个或多个集成电路，例如：一个或多个特定集成电路(Application Specific Integrated Circuit，ASIC)，或，一个或多个微处理器(digital singnal processor，DSP)，或，一个或者多个现场可编程门阵列(Field Programmable Gate Array，FPGA)等。再如，当以上某个模块通过处理元件调度程序的形式实现时，该处理元件可以是通用处理器， 例如中央处理器(Central Processing Unit，CPU)或其它可以调用程序的处理器。再如，这些模块可以集成在一起，以片上系统(system-on-a-chip，SOC)的形式实现。
另一方面，本申请实施例还提供一种图像处理装置，包括：处理器和存储器，存储器用于存储至少一条指令，指令由处理器加载并执行时以实现上述的图像处理方法。该图像处理装置可以应用上述的图像处理方法，具体过程和原理不再赘述。
处理器的数量可以为一个或多个，处理器和存储器可以通过总线或者其他方式连接。存储器作为一种非暂态计算机可读存储介质，可用于存储非暂态软件程序、非暂态计算机可执行程序以及模块，如本申请实施例中的图像检测方法对应的程序指令/模块。处理器通过运行存储在存储器中的非暂态软件程序、指令以及模块，从而执行各种功能应用以及数据处理，即实现上述任意方法实施例中的方法。存储器可以包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需要的应用程序；以及必要数据等。此外，存储器可以包括高速随机存取存储器，还可以包括非暂态存储器，例如至少一个磁盘存储器件、闪存器件、或其他非暂态固态存储器件。
本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质中存储有计算机程序，当其在计算机上运行时，使得计算机执行上述实施例的图像处理方法。
在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。所述计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行所述计算机程序指令时，全部或部分地产生按照本申请所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，所述计算机指 令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线)或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质，(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘Solid State Disk)等。
本申请实施例中，“至少一个”是指一个或者多个，“多个”是指两个或两个以上。“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示单独存在A、同时存在A和B、单独存在B的情况。其中A，B可以是单数或者复数。字符“/”一般表示前后关联对象是一种“或”的关系。“以下至少一项”及其类似表达，是指的这些项中的任意组合，包括单项或复数项的任意组合。例如，a，b和c中的至少一项可以表示：a,b,c,a-b,a-c,b-c,或a-b-c，其中a,b,c可以是单个，也可以是多个。
以上仅为本申请的优选实施例而已，并不用于限制本申请，对于本领域的技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本申请的保护范围之内。

Claims (10)

  1. 一种图像处理方法，其特征在于，包括：
    获取WRGB色彩滤波阵列CFA图像；
    将所述WRGB CFA图像转换为拜耳Bayer图像；
    将所述Bayer图像转换为全分辨率的RGB图像；
    在所述WRGB CFA图像中的R通道位置、G通道位置和B通道位置中插值W通道数据，生成全分辨率的W通道图像；
    将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像。
  2. 根据权利要求1所述的图像处理方法，其特征在于，
    所述将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像的过程包括：
    将所述全分辨率的RGB图像作为待融合图像，使所述待融合图像和所述全分辨率的W通道图像进行融合，得到融合后的图像；
    对所述融合后的图像进行颜色还原。
  3. 根据权利要求1所述的图像处理方法，其特征在于，
    所述将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像的过程包括：
    对所述全分辨率的RGB图像进行颜色还原，得到颜色还原后的图像；
    将所述颜色还原后的图像作为待融合图像，使所述待融合图像和所述全分辨率的W通道图像进行融合。
  4. 根据权利要求1所述的图像处理方法，其特征在于，
    所述将所述WRGB CFA图像转换为拜耳Bayer图像的过程包括：
    获取所述WRGB CFA图像在W通道位置的W通道采样图，以及获取WRGB CFA图像在G通道位置的G通道采样图；
    对所述W通道采样图在G通道位置插值W通道得到W插值图；
    以所述W插值图为导向图，对所述G通道采样图进行导向滤波处理，得到G通道初始估计值；
    根据所述G通道采样图生成残差；
    将所述残差在W通道位置进行插值，得到插值后的残差，将所述插值后的残差与所述G通道初始估计值相加，得到G通道插值图；
    根据所述G通道插值图和所述WRGB CFA图像中的R通道及B通道，得到还原后的所述Bayer图像。
  5. 根据权利要求4所述的图像处理方法，其特征在于，
    所述残差为
    Figure PCTCN2020107480-appb-100001
    其中，M G为二值图，二值图的G通道位置数据值为1，其他位置的数据值为0，G sub为所述G通道采样图，
    Figure PCTCN2020107480-appb-100002
    为所述G通道初始估计值。
  6. 根据权利要求2或3所述的图像处理方法，其特征在于，
    所述使所述待融合图像和所述全分辨率的W通道图像进行融合的过程包括：
    将所述待融合图像从RGB色彩空间转换为YCbCr色彩空间，得到转换后的待融合图像；
    以所述转换后的待融合图像中的Y分量为导向图，对所述全分辨率的W通道图像进行导向滤波处理，得到W通道初始估计值；
    将所述转换后的待融合图像中的Y分量替换为所述W通道初始估计值，得到替换后的待融合图像；
    将所述替换后的待融合图像从YCbCr色彩空间转换为RGB色彩空间。
  7. 根据权利要求2、3和6中任意一项所述的图像处理方法，其特征在于，
    所述颜色还原包括以下各项之一或任意组合：
    自动白平衡、色彩校正矩阵处理、伽玛校正和色调曲线调节。
  8. 一种图像处理装置，其特征在于，包括：
    图像获取模块，用于获取WRGB色彩滤波阵列CFA图像；
    转换模块，用于将所述WRGB CFA图像转换为拜耳Bayer图像以及将所述Bayer图像转换为全分辨率的RGB图像；
    处理模块，用于在所述WRGB CFA图像中的R通道位置、G通 道位置和B通道位置中插值W通道数据，生成全分辨率的W通道图像；
    结合模块，用于将所述全分辨率的RGB图像和所述全分辨率的W通道图像进行结合，得到结合后的RGB图像。
  9. 一种图像处理装置，其特征在于，包括：
    处理器和存储器，所述存储器用于存储至少一条指令，所述指令由所述处理器加载并执行时以实现如权利要求1至7中任意一项所述的图像处理方法。
  10. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有计算机程序，当其在计算机上运行时，使得计算机执行如权利要求1至7中任意一项所述的图像处理方法。
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