CN118368534A - Image optimization method and device, electronic equipment and storage medium - Google Patents
Image optimization method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN118368534A CN118368534A CN202410756465.3A CN202410756465A CN118368534A CN 118368534 A CN118368534 A CN 118368534A CN 202410756465 A CN202410756465 A CN 202410756465A CN 118368534 A CN118368534 A CN 118368534A
- Authority
- CN
- China
- Prior art keywords
- pixel
- sub
- image
- coordinates
- camera
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 46
- 238000005457 optimization Methods 0.000 title abstract description 22
- 238000003384 imaging method Methods 0.000 claims abstract description 49
- 238000003491 array Methods 0.000 claims abstract description 21
- 238000012937 correction Methods 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 4
- 230000015572 biosynthetic process Effects 0.000 claims description 3
- 238000000354 decomposition reaction Methods 0.000 claims description 3
- 238000003786 synthesis reaction Methods 0.000 claims description 3
- 239000006185 dispersion Substances 0.000 abstract description 10
- 230000000694 effects Effects 0.000 abstract description 4
- 230000008569 process Effects 0.000 abstract description 4
- 238000012545 processing Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000009877 rendering Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
Landscapes
- Color Television Image Signal Generators (AREA)
Abstract
The application provides an image optimization method, an image optimization device, electronic equipment and a storage medium, and relates to the technical field of image processing, wherein the method comprises the steps of decomposing a first image acquired by a camera into first pixel arrays corresponding to R, G, B color channels respectively; for each first pixel array, correcting pixel coordinates and sub-pixel values of all sub-pixel points of the first pixel array based on the refractive index of the color channel by a lens of a camera so as to generate a corresponding second pixel array; and combining the second pixel arrays corresponding to the R, G, B color channels respectively to obtain an optimized second image, so as to optimize the dispersion effect of the image in the imaging process of the camera, and enable the imaging of the camera to be closer to a real scene.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to an image optimization method, an image optimization device, an electronic device, and a storage medium.
Background
In the process of imaging a camera, there are many parameters affecting imaging quality, wherein the refractive index difference of the lens for different wavelengths can cause a chromatic dispersion effect on the picture. In some application scenes with high requirements on the real-time performance and the authenticity of picture output, such as automatic driving simulation, a dispersion picture can influence the rendering effect in the scene simulation, so that the optimization of the dispersion picture is a technical problem to be solved.
Disclosure of Invention
The embodiment of the application aims to provide an image optimization method, an image optimization device, electronic equipment and a storage medium, which are used for optimizing the dispersion effect of an image in the imaging process of a camera so that the imaging of the camera is closer to a real scene.
In a first aspect, the present application provides an image optimization method, including decomposing a first image acquired by a camera into first pixel arrays corresponding to R, G, B color channels, respectively; for each first pixel array, correcting pixel coordinates and sub-pixel values of all sub-pixel points of the first pixel array based on the refractive index of the color channel by a lens of a camera so as to generate a corresponding second pixel array; and combining the second pixel arrays corresponding to the R, G, B color channels respectively to obtain an optimized second image.
Preferably, for any one of the first pixel arrays corresponding to R, G, B color channels, a corresponding second pixel array is generated by:
Determining preset pixel coordinates of each sub-pixel point in the first pixel array according to the original pixel coordinates and the corresponding color channel imaging proportion of the sub-pixel point; determining a sub-pixel value of the target pixel coordinate based on the preset pixel coordinate of each sub-pixel point and the corresponding sub-pixel value; and generating a second pixel array based on all the target pixel coordinates and the sub-pixel values corresponding to the target pixel coordinates.
Preferably, for each sub-pixel point, the preset pixel coordinates of the sub-pixel value are determined by:
；
Wherein, Is the original pixel coordinates of the sub-pixel point,The preset pixel coordinates for the sub-pixel points,Is the center point pixel coordinates of the first image,And imaging the corresponding color channel of the first pixel array.
Preferably, the target pixel coordinates are determined by:
for each preset pixel coordinate Rounding the abscissa and the ordinate in the preset pixel coordinates to obtain a corresponding target pixel coordinate; And determining a sub-pixel value for each target pixel coordinate by:
；
Wherein, And the sub-pixel value corresponding to the preset pixel coordinate is obtained.
Preferably, the color channel imaging ratio corresponding to the R, G, B three color channels is determined in the following manner:
acquiring a focal length corresponding wavelength of a camera; and respectively calculating imaging proportion values corresponding to the three color channels R, G, B based on the corresponding wavelength of the focal length and a preset calculation rule.
Preferably, the imaging scale value corresponding to each of R, G, B color channels is calculated by:
；
；
；
；
Wherein, For the focal length corresponding wavelength, a is the intermediate imaging scale value,The imaging scale value corresponding to the G color channel,For the imaging scale value corresponding to the R color channel,And the imaging proportion value corresponding to the B color channel.
Preferably, the size of the first image is larger than the size of the second image.
In a second aspect, the present application provides an image optimizing apparatus, the apparatus comprising:
The decomposition module is used for decomposing the first image acquired by the camera into first pixel arrays corresponding to the R, G, B color channels respectively;
The correction module is used for correcting pixel coordinates and sub-pixel values of all sub-pixel points of each first pixel array based on the refractive index of the color channel by the lens of the camera so as to generate a corresponding second pixel array;
and the synthesis module is used for combining the second pixel arrays corresponding to the R, G, B color channels respectively so as to acquire an optimized second image.
In a third aspect, the present application provides an electronic device, comprising: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory are communicated through the bus, and the processor executes the machine-readable instructions to execute the steps of the optimization method of the image.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of optimizing an image as described above.
The application provides an image optimization method, an image optimization device, electronic equipment and a storage medium, wherein the method comprises the steps of decomposing a first image acquired by a camera into first pixel arrays corresponding to R, G, B color channels respectively; for each first pixel array, correcting pixel coordinates and sub-pixel values of all sub-pixel points of the first pixel array based on the refractive index of the color channel by a lens of a camera so as to generate a corresponding second pixel array; and combining the second pixel arrays corresponding to the R, G, B color channels respectively to obtain an optimized second image. The image is processed by using the camera parameters which are easy to obtain, so that the chromatic dispersion problem of camera imaging is optimized, and the image processing method has good controllability.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of an image optimization method according to an embodiment of the present application;
FIG. 2 is a flowchart illustrating steps for modifying a pixel array according to an embodiment of the present application;
FIG. 3 is a schematic structural diagram of an image optimizing apparatus according to an embodiment of the present application;
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
First, an application scenario of the present application will be described. The technical scheme of the application can be applied to the optimization of chromatic dispersion after the image sensor acquires the image.
Taking the camera as an example, the focal length of the camera is fixed, but since the refractive index of the lens of the camera is different for light rays with different wavelengths, the wavelength of the best imaging actually corresponds to the fixed focal length of the camera is only one. Therefore, during the imaging process of the camera, light with other wavelengths corresponds to different refractive indexes, and thus chromatic dispersion occurs in the picture.
Accordingly, the application provides an image optimization method, an image optimization device, electronic equipment and a storage medium.
The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.
Fig. 1 is a flowchart of an image optimization method according to an embodiment of the present application. The image optimization method provided by the embodiment of the application specifically comprises the following steps:
S1, decomposing a first image acquired by a camera into first pixel arrays corresponding to R, G, B color channels respectively.
Each first pixel array may include pixel coordinates of all pixel points and sub-pixel values on corresponding color channels.
S2, for each first pixel array, correcting pixel coordinates and sub-pixel values of all sub-pixel points of the first pixel array based on the refractive index of the color channel by a lens of the camera so as to generate a corresponding second pixel array.
Fig. 2 is a flowchart illustrating a procedure for correcting a pixel array according to an embodiment of the present application. In step S2, for any one of the first pixel arrays corresponding to R, G, B color channels, a corresponding second pixel array is generated by:
s20, determining preset pixel coordinates of each sub-pixel point in the first pixel array according to the original pixel coordinates and the corresponding color channel imaging proportion of the sub-pixel point.
For each sub-pixel point, determining preset pixel coordinates of the sub-pixel value by the following method:
；
Wherein, Is the original pixel coordinates of the sub-pixel point,The preset pixel coordinates for the sub-pixel points,Is the center point pixel coordinates of the first image,And imaging the corresponding color channel of the first pixel array.
And determining R, G, B color channel imaging ratios corresponding to the three color channels by:
acquiring a focal length corresponding wavelength of a camera; and respectively calculating imaging proportion values corresponding to the three color channels R, G, B based on the corresponding wavelength of the focal length and a preset calculation rule.
The focal length corresponding wavelength is set according to the focal length of the camera, and can be determined by factory parameters of the camera.
According to the optical principle, the focal length of the camera is generally 380nm-740nm, the intermediate value 560nm is the wavelength corresponding to the standard green, the standard blue is 470nm, and the standard red is 650nm. And calculating a new pixel array corresponding to the three RGB color channels according to the input wavelength lambda corresponding to the focal length and the change of the RGB data of the original image obtained by interpolation fitting of the wavelength corresponding to the RGB color.
The zoom-in or zoom-out ratio of the three color channel imaging is calculated. Taking the longest wavelength imaging scale value of 0.9 and the shortest wavelength imaging scale value of 1.1 as an example, the imaging scale values corresponding to the R, G, B color channels can be calculated by the following linear interpolation method:
；
；
；
；
Wherein, For the focal length corresponding wavelength, a is the intermediate imaging scale value,The imaging scale value corresponding to the G color channel,For the imaging scale value corresponding to the R color channel,And the imaging proportion value corresponding to the B color channel.
S22, determining the sub-pixel value of the target pixel coordinate based on the preset pixel coordinate of each sub-pixel point and the corresponding sub-pixel value.
Since dispersion causes a pixel position shift, the coordinates of each pixel point are recalculated in step S22. And assuming that the center point corresponding to the lens is not offset, namely the pixel coordinate of the center point in the picture is the focusing center. For each sub-pixel point, determining preset pixel coordinates of the sub-pixel value by the following method:
；
Wherein, Is the original pixel coordinates of the sub-pixel point,The preset pixel coordinates for the sub-pixel points,Is the center point pixel coordinates of the first image,And imaging the corresponding color channel of the first pixel array.
S24, generating a second pixel array based on all the target pixel coordinates and the sub-pixel values corresponding to the target pixel coordinates.
Since the pixel coordinates of each pixel point in step S22 are not necessarily integer values, the corresponding sub-pixel values on the integer pixel points cannot be directly determined. Specifically, the target pixel coordinates may be determined by:
for each preset pixel coordinate Rounding the abscissa and the ordinate in the preset pixel coordinates to obtain a corresponding target pixel coordinate。
And determining a sub-pixel value for each target pixel coordinate by interpolation:
；
Wherein, And the sub-pixel value corresponding to the preset pixel coordinate is obtained.
It will be appreciated that a pixel may be deleted if its coordinates fall outside the original image size.
S3, combining second pixel arrays corresponding to the R, G, B color channels respectively to obtain an optimized second image.
And finally, combining the second pixel arrays corresponding to the three corrected color channels respectively to obtain a new second image.
In the embodiment of the application, the image is processed by using the camera parameters which are easy to obtain, so that the chromatic dispersion problem of camera imaging is optimized, the method has good controllability, and the application range is wide only by adjusting the parameters in the calculation model.
In one embodiment of the present application, the position of the pixel point in the image is shifted, which may result in the loss of the edge pixel of the original image, so that the size of the first image is larger than the size of the second image in order to ensure the integrity of the output image. I.e. a camera having an imaging size larger than the size of the second image to be used can be selected for acquisition of the second image.
In a specific embodiment of the present application, the foregoing image optimization method may be applied to the automatic driving technology of the vehicle. I.e. the camera in step S1 may be an onboard camera. The optimized second image is used for rendering the scene in the automatic driving simulation.
Fig. 3 is a schematic structural diagram of an image optimizing apparatus according to an embodiment of the present application. Based on the same inventive concept, the embodiment of the present application further provides an image optimizing apparatus 300, where the apparatus includes:
The decomposition module 310 is configured to decompose a first image acquired by the camera into first pixel arrays corresponding to R, G, B color channels respectively;
a correction module 320, configured to correct, for each first pixel array, pixel coordinates and sub-pixel values of all sub-pixel points of the first pixel array based on a refractive index of the color channel by a lens of the camera, so as to generate a corresponding second pixel array;
and the synthesis module 330 is configured to combine the second pixel arrays corresponding to the R, G, B color channels respectively, so as to obtain an optimized second image.
In a preferred embodiment, for any one of the first pixel arrays corresponding to R, G, B color channels, the correction module 320 generates a corresponding second pixel array by:
Determining preset pixel coordinates of each sub-pixel point in the first pixel array according to the original pixel coordinates and the corresponding color channel imaging proportion of the sub-pixel point; determining a sub-pixel value of the target pixel coordinate based on the preset pixel coordinate of each sub-pixel point and the corresponding sub-pixel value; and generating a second pixel array based on all the target pixel coordinates and the sub-pixel values corresponding to the target pixel coordinates.
In a preferred embodiment, for each sub-pixel, the correction module 320 determines the preset pixel coordinates for the sub-pixel value by:
；
Wherein, Is the original pixel coordinates of the sub-pixel point,The preset pixel coordinates for the sub-pixel points,Is the center point pixel coordinates of the first image,And imaging the corresponding color channel of the first pixel array.
In a preferred embodiment, the correction module 320 determines the target pixel coordinates by:
for each preset pixel coordinate Rounding the abscissa and the ordinate in the preset pixel coordinates to obtain a corresponding target pixel coordinate; And determining a sub-pixel value for each target pixel coordinate by:
；
Wherein, And the sub-pixel value corresponding to the preset pixel coordinate is obtained.
In a preferred embodiment, the correction module 320 is further configured to:
and acquiring the corresponding wavelength of the focal length of the camera, and respectively calculating imaging proportion values corresponding to the three color channels R, G, B based on the corresponding wavelength of the focal length and a preset calculation rule.
In a preferred embodiment, the correction module 320 calculates R, G, B the imaging scale values corresponding to each of the three color channels by:
；
；
；
；
Wherein, For the focal length corresponding wavelength, a is the intermediate imaging scale value,The imaging scale value corresponding to the G color channel,For the imaging scale value corresponding to the R color channel,And the imaging proportion value corresponding to the B color channel.
In a preferred embodiment, the size of the first image is larger than the size of the second image.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the application. As shown in fig. 4, the electronic device 400 includes a processor 410, a memory 420, and a bus 430.
The memory 420 stores machine-readable instructions executable by the processor 410, and when the electronic device 400 is running, the processor 410 communicates with the memory 420 through the bus 430, and when the machine-readable instructions are executed by the processor 410, the steps of an image optimization method in the method embodiment shown in fig. 1 can be executed, and a specific implementation manner may refer to the method embodiment and will not be described herein.
The embodiment of the present application further provides a computer readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps of an image optimization method in the embodiment of the method shown in fig. 1 may be executed, and a specific implementation manner may refer to the embodiment of the method and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
Further, the units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Furthermore, functional modules in various embodiments of the present application may be integrated together to form a single portion, or each module may exist alone, or two or more modules may be integrated to form a single portion.
It should be noted that the functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM) random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and variations will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method of optimizing an image, the method comprising:
The first image acquired by the camera is decomposed into first pixel arrays corresponding to R, G, B color channels respectively;
For each first pixel array, correcting pixel coordinates and sub-pixel values of all sub-pixel points of the first pixel array based on the refractive index of the color channel by a lens of a camera so as to generate a corresponding second pixel array;
And combining the second pixel arrays corresponding to the R, G, B color channels respectively to obtain an optimized second image.
2. The method of claim 1, wherein for any one of the first pixel arrays corresponding to R, G, B color channels, a corresponding second pixel array is generated by:
Determining preset pixel coordinates of each sub-pixel point in the first pixel array according to the original pixel coordinates and the corresponding color channel imaging proportion of the sub-pixel point;
determining a sub-pixel value of the target pixel coordinate based on the preset pixel coordinate of each sub-pixel point and the corresponding sub-pixel value;
and generating a second pixel array based on all the target pixel coordinates and the sub-pixel values corresponding to the target pixel coordinates.
3. The method of claim 2, wherein for each sub-pixel point, the preset pixel coordinates of the sub-pixel value are determined by:
；
Wherein, Is the original pixel coordinates of the sub-pixel point,The preset pixel coordinates for the sub-pixel points,Is the center point pixel coordinates of the first image,And imaging the corresponding color channel of the first pixel array.
4. The method of claim 2, wherein the target pixel coordinates are determined by:
for each preset pixel coordinate Rounding the abscissa and the ordinate in the preset pixel coordinates to obtain a corresponding target pixel coordinate; And
The subpixel value for each target pixel coordinate is determined by:
；
Wherein, And the sub-pixel value corresponding to the preset pixel coordinate is obtained.
5. The method as recited in claim 2, further comprising:
acquiring a focal length corresponding wavelength of a camera;
And respectively calculating imaging proportion values corresponding to the R, G, B color channels based on the wavelength corresponding to the focal length and a preset calculation rule.
6. The method of claim 5, wherein the imaging scale values for each of the R, G, B color channels are calculated by:
；
；
；
；
Wherein, For the focal length corresponding wavelength, a is the intermediate imaging scale value,The imaging scale value corresponding to the G color channel,For the imaging scale value corresponding to the R color channel,And the imaging proportion value corresponding to the B color channel.
7. The method of claim 1, wherein the first image has a size that is larger than a size of the second image.
8. An image optimizing apparatus, characterized in that the apparatus comprises:
The decomposition module is used for decomposing the first image acquired by the camera into first pixel arrays corresponding to the R, G, B color channels respectively;
The correction module is used for correcting pixel coordinates and sub-pixel values of all sub-pixel points of each first pixel array based on the refractive index of the color channel by the lens of the camera so as to generate a corresponding second pixel array;
and the synthesis module is used for combining the second pixel arrays corresponding to the R, G, B color channels respectively so as to acquire an optimized second image.
9. An electronic device, comprising: a processor, a memory and a bus, said memory storing machine readable instructions executable by said processor, said processor and said memory communicating over the bus when the electronic device is running, said processor executing said machine readable instructions to perform the steps of the method of optimizing an image according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, performs the steps of the method of optimizing an image according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410756465.3A CN118368534B (en) | 2024-06-13 | 2024-06-13 | Image optimization method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410756465.3A CN118368534B (en) | 2024-06-13 | 2024-06-13 | Image optimization method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118368534A true CN118368534A (en) | 2024-07-19 |
| CN118368534B CN118368534B (en) | 2024-08-27 |
Family
ID=91881482
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410756465.3A Active CN118368534B (en) | 2024-06-13 | 2024-06-13 | Image optimization method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118368534B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110141321A1 (en) * | 2009-12-16 | 2011-06-16 | General Instrument Corporation | Method and apparatus for transforming a lens-distorted image to a perspective image in bayer space |
| CN113971635A (en) * | 2021-10-27 | 2022-01-25 | 深圳锐视智芯科技有限公司 | Image array format conversion method and device, electronic equipment and storage medium |
| CN114695408A (en) * | 2020-12-31 | 2022-07-01 | 三星电子株式会社 | Image sensor including planar nanophotonic microlens array and electronic device including the same |
| CN115103168A (en) * | 2022-06-27 | 2022-09-23 | 展讯通信（上海）有限公司 | Image generation method, image generation device, electronic equipment and storage medium |
| CN116582759A (en) * | 2023-04-11 | 2023-08-11 | 北京奕斯伟计算技术股份有限公司 | Image processing device, method, electronic device, and medium |
| CN117425091A (en) * | 2022-03-28 | 2024-01-19 | 荣耀终端有限公司 | Image processing method and electronic equipment |
-
2024
- 2024-06-13 CN CN202410756465.3A patent/CN118368534B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110141321A1 (en) * | 2009-12-16 | 2011-06-16 | General Instrument Corporation | Method and apparatus for transforming a lens-distorted image to a perspective image in bayer space |
| CN114695408A (en) * | 2020-12-31 | 2022-07-01 | 三星电子株式会社 | Image sensor including planar nanophotonic microlens array and electronic device including the same |
| CN113971635A (en) * | 2021-10-27 | 2022-01-25 | 深圳锐视智芯科技有限公司 | Image array format conversion method and device, electronic equipment and storage medium |
| CN117425091A (en) * | 2022-03-28 | 2024-01-19 | 荣耀终端有限公司 | Image processing method and electronic equipment |
| CN115103168A (en) * | 2022-06-27 | 2022-09-23 | 展讯通信（上海）有限公司 | Image generation method, image generation device, electronic equipment and storage medium |
| CN116582759A (en) * | 2023-04-11 | 2023-08-11 | 北京奕斯伟计算技术股份有限公司 | Image processing device, method, electronic device, and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118368534B (en) | 2024-08-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP1512123B1 (en) | System and method for electronic correction of optical anomalies | |
| CN101884222B (en) | The image procossing presented for supporting solid | |
| US7443392B2 (en) | Image processing program for 3D display, image processing apparatus, and 3D display system | |
| CN102844788B (en) | Image processing apparatus and use the image pick-up device of this image processing apparatus | |
| US8477206B2 (en) | Image processing apparatus and image processing method for performing image restoration using restoration filter | |
| EP1528793B1 (en) | Image processing apparatus, image-taking system and image processing method | |
| US8565524B2 (en) | Image processing apparatus, and image pickup apparatus using same | |
| KR20070065112A (en) | Apparatus and method for color correction | |
| JP2007304525A (en) | Image input device, electronic equipment, and image input method | |
| CN105681680A (en) | Image vignetting correction method, device and system | |
| JP6991957B2 (en) | Image processing device, image pickup device and image processing method | |
| CN105323423A (en) | Image processing method, image processing apparatus, and image pickup apparatus | |
| JP5479187B2 (en) | Image processing apparatus and imaging apparatus using the same | |
| JP4891301B2 (en) | Image processing method, image processing apparatus, and imaging apparatus | |
| EP2541941B1 (en) | Axial chromatic aberration correction | |
| CN118368534B (en) | Image optimization method and device, electronic equipment and storage medium | |
| JP5268533B2 (en) | Image processing method, image processing apparatus, imaging apparatus, and image processing program | |
| US8953069B2 (en) | Image capturing module and image capturing apparatus with multiple image capturing systems of multiple wavelength regions | |
| JP5330291B2 (en) | Signal processing apparatus and imaging apparatus | |
| CN114529460A (en) | Low-illumination-scene intelligent highway monitoring rapid defogging method and device and electronic equipment | |
| JP2022161503A (en) | Image processing method, method of manufacturing machine learning model, image processing apparatus, image processing system, and program | |
| CN112468795B (en) | Method and device for adjusting white balance of camera | |
| CN116416310A (en) | Method and device for optimizing light transmission area structure of under-screen camera and electronic device | |
| JP5197839B2 (en) | Image processing method, image processing apparatus, imaging apparatus, and program | |
| CN114926364A (en) | Image correction method, image correction device, computer equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |