Image effect processing method and device and computer device

Abstract

The present application provides an image effect processing method, the image is an image processed by an ISP, and the method comprises the following steps: obtaining RAW image data with poor image effect; performing format conversion on the RAW image data to obtain multiple RAW image data in different formats; inputting the multiple RAW image data into multiple different processing platforms one by one for ISP simulation processing to obtain multiple images, each processing platform supporting one format of RAW image data; comparing the effects of the multiple images; if the effects of the multiple images are the same, determining that the poor image effect is caused by the RAW image data; and if the effects of the multiple images are different, determining that the poor image effect is caused by the ISP of the processing platform. In addition, the present application also provides an image effect processing device and a computer device. The present application can trace the cause of poor image effect without professional detection equipment, thereby effectively saving detection cost.

Description

Technical Field

[0001] This invention relates to the field of image detection technology, and in particular to an image effect processing method, computer equipment, and apparatus. Background Technology

[0002] Currently, images acquired by raw image sensors need to be processed by the platform's image signal processor (ISP) to obtain the final image. Typically, raw image data is input into the ISP of a processing platform to produce the corresponding image. However, the resulting image may have issues such as insufficient or excessive resolution, underexposure, excessive sharpening, or the presence of unwanted objects. Identifying the cause of these problems allows for their correction.

[0003] However, image problems may be caused by the ISP image processor or by the raw image data, which is difficult to distinguish with the naked eye. Therefore, additional detection equipment is needed to detect problems in the ISP and the raw image data, but additional professional detection equipment will increase costs. Summary of the Invention

[0004] This invention provides an image effect processing method, computer equipment, and apparatus that can trace the cause of image problems without the need for specialized testing equipment, greatly saving on problem detection costs.

[0005] In a first aspect, embodiments of the present invention provide an image effect processing method, wherein the image is an image processed by an ISP (Image Signal Processor). The image effect processing method includes: acquiring RAW image data with poor image effect; converting the RAW image data to obtain multiple RAW image data in different formats; inputting the multiple RAW image data into multiple different processing platforms for ISP simulation processing to obtain several images, each processing platform supporting one format of RAW image data; comparing whether the effects of the several images are the same; if the effects of the several images are the same, determining that the poor image effect is caused by the RAW image data; if the effects of the several images are different, determining that the poor image effect is caused by the ISP of the processing platform.

[0006] Secondly, embodiments of the present invention provide an image effect processing apparatus, comprising an acquisition unit, a conversion unit, an input unit, a comparison unit, a first judgment unit, and a second judgment unit. The acquisition unit is used to acquire RAW image data with poor image quality. The conversion unit is used to convert the RAW image data into multiple RAW image data in different formats. The input unit is used to input the multiple RAW image data into multiple different processing platforms for ISP simulation processing to obtain several images, each processing platform supporting one RAW image data format. The comparison unit is used to compare whether the effects of the several images are the same. The first judgment unit is used to determine that if the effects of the several images are the same, the poor image quality is caused by the RAW image data. The second judgment unit is used to determine that if the effects of the several images are different, the poor image quality is caused by the ISP of the processing platform.

[0007] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor. The memory is used to store a computer-executable program. The processor is used to execute the computer-executable program to implement the image effect processing method as described above.

[0008] Fourthly, embodiments of the present invention provide a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the image effect processing method as described above.

[0009] In the above embodiments, by analyzing the raw data of images with poor quality, the raw data of the images are input into ISPs of different processing platforms for processing. The image quality output by the ISPs of different processing platforms is then examined. By comparing whether the output image quality is consistent, it is determined whether the cause of the poor image quality is from the ISP or the raw image data. This effectively traces the true cause of the image problem without the need for additional professional testing equipment to detect problems in the ISP and the raw image data, thus saving costs. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0011] Figure 1 This is a schematic flowchart of the image effect processing method provided in the first embodiment of the present invention.

[0012] Figure 2 This is a schematic diagram of the first sub-process of the image effect processing method provided in the first embodiment of the present invention.

[0013] Figure 3 This is a schematic diagram of the second sub-process of the image effect processing method provided in the first embodiment of the present invention.

[0014] Figure 4 This is a schematic flowchart of the image effect processing method provided in the second embodiment of the present invention.

[0015] Figure 5 This is a schematic diagram of the third sub-process of the image effect processing method provided in the first embodiment of the present invention.

[0016] Figure 6 This is a schematic diagram of the image effect processing device module provided in the first embodiment of the present invention.

[0017] Figure 7 This is a schematic diagram of the image generation unit provided in the first embodiment of the present invention.

[0018] Figure 8 This is a schematic diagram of the internal structure of a computer device provided in the first embodiment of the present invention.

[0019] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0021] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar planned objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data are interchangeable where appropriate; in other words, the described embodiments are implemented according to a sequence other than that illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, may also include other content; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] It should be noted that the descriptions involving "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include one or more of that feature. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0023] Please refer to Figure 1 This is a schematic flowchart of the image effect processing method provided in the first embodiment of the present invention. The image effect processing method is used to analyze the cause of problems in images processed by the ISP when such problems occur. The image effect processing method specifically includes the following steps.

[0024] Step S101: Obtain RAW image data with poor image quality.

[0025] In step S101, the RAW image data is image-related data obtained directly from the shooting device, without any processing other than simple magnification and analog-to-digital conversion. This includes sensor metadata, sensor size, color attributes, configuration files, and other information. In this embodiment, when the image processed by the ISP image processor does not achieve the expected effect, the RAW image data of the poorly processed image is obtained, which is the original data of the image. Understandably, the expected effect can include, but is not limited to, situations such as excessively low or high resolution, insufficient or insufficient exposure, excessive sharpening, and the presence of foreign objects in the image.

[0026] Step S102: Convert the RAW image data into multiple RAW image data in different formats.

[0027] Poor image quality can be caused by a problem with the ISP used to process the RAW image data, or it could be due to a problem with the RAW image data itself. To quickly determine whether the poor image quality is caused by the ISP, the RAW image data can be processed using one or more other ISPs. Since multiple different ISPs encountered problems processing the same RAW image data, the probability that the RAW image data itself is faulty is quite high. Therefore, in this embodiment, it is necessary to process the RAW image data using an additional ISP. Preferably, the additional ISP uses an image processing platform with a different format supported by the ISP that generated the problematic image.

[0028] In step S102, in order for the RAW image data to be recognized or supported by other ISPs, it is necessary to convert the format of the RAW image data. Understandably, the format conversion of the RAW image data can be achieved using existing conversion tools, and will not be elaborated upon here.

[0029] Step S103: Input the multiple RAW image data into multiple different processing platforms one by one to perform ISP simulation processing to obtain several images. Each processing platform supports a RAW image data format.

[0030] Specifically, after RAW image data is converted into multiple RAW image data supported by multiple different ISPs, the multiple RAW image data are respectively input into multiple different processing platforms for ISP simulation processing to obtain multiple images. Understandably, each ISP supports one or more different formats of RAW image data.

[0031] Step S104: Compare whether the effects of the several images are the same.

[0032] In step S103, after the RAW image data is processed by the ISP simulation of different processing platforms to obtain multiple images corresponding to the processing platform, the imaging effect of the multiple images is compared. In this embodiment, the effect can be compared from multiple aspects such as the exposure, sharpness, color difference, image clarity, color, and illumination uniformity of the image. Understandably, the ISPs of the different processing platforms are ISPs from different manufacturers, such as Fuji, Canon, Kodak, and Nikon.

[0033] Step S105: If the effects of the several images are the same, it is determined that the poor image effect is caused by the RAW image data.

[0034] Specifically, if problems occur when processing the same RAW image data using multiple different ISPs, it indicates a high probability that the RAW image data itself is faulty. In step S104, when comparing the imaging effects of the generated images from multiple angles, if the imaging effects of each image are consistent, it indicates that the cause of the image effect problem is the RAW image data. In this case, it can be determined that the problem lies with the RAW image data. In some feasible embodiments, professional image analysis software can be used to analyze the effects of images output by different ISPs and print out an analysis report to help staff better understand the true cause of the image effect problem.

[0035] Step S106: If the effects of the several images are different, it is determined that the poor image effect is caused by the ISP of the processing platform.

[0036] Specifically, if the image effects output by ISP image processors of different processing platforms are inconsistent, it is highly likely that the poor image effect is caused by the ISP image processor. In some feasible embodiments, the imaging effect can be compared from multiple angles of the image. However, when comparing the effects, multiple images are compared from one angle in turn until an image with different effects at the same angle is found. Based on the image, the corresponding processing platform is found, thereby finding the ISP that is causing the poor image effect.

[0037] In the above embodiments, one or more ISPs are used to simulate and process the RAW image data of the image with poor effect to obtain several images. By comparing the effects of several images, it is quickly determined whether the cause of poor image effect is caused by the ISP or the RAW image data. This effectively traces the real cause of poor image effect without the need for additional professional testing equipment to detect problems with the ISP and the original image data, thus saving costs.

[0038] Please refer to Figure 2 This is a schematic diagram of the first sub-process of the image effect processing method provided in the first embodiment of the present invention. After determining that the cause of poor image effect is RAW image data, the imaging module that acquires RAW image data will be analyzed. The analysis process specifically includes the following steps.

[0039] Step S201: Using an imaging module that acquires the RAW image data, multiple test RAW image data sets are obtained from different angles under the same color temperature conditions. The imaging module includes an imaging sensor and a lens.

[0040] Specifically, the same color temperature is a preset color temperature, such as LED lamps, halogen lamps, fluorescent lamps, and incandescent lamps. The imaging model captures multiple test RAW image data from light sources of the same color temperature but in different directions. Understandably, there are multiple imaging modules, and each imaging module includes an imaging sensor and a lens.

[0041] Step S202: Analyze the multiple test RAW image data to determine whether the poor image quality is caused by the lens or the imaging sensor in the imaging module.

[0042] Specifically, we analyzed multiple sets of test RAW image data to determine the root cause of poor image quality, identifying problematic components including the lens and imaging sensor. The analysis process will be described in detail in the following steps.

[0043] In the above embodiments, by analyzing the imaging module that acquires RAW image data, the real cause of poor image quality is found, reducing repetitive problems generated during image debugging and further saving the detection cost of problematic images.

[0044] Please refer to Figure 3 This is a schematic diagram of the second sub-process of the image effect processing method provided in the first embodiment of the present invention. The step of using the imaging module that acquires the RAW image data to capture multiple test RAW image data from different angles under the same color temperature conditions specifically includes the following steps.

[0045] Step S301: Control the light source to emit the same light under the preset scene.

[0046] Specifically, the same light is a preset light, including but not limited to light emitted by LED lamps, halogen lamps, fluorescent lamps, and incandescent lamps.

[0047] Step S302: Under the preset scene, the imaging module is sequentially adjusted to different viewing angles and then photographed to obtain the multiple test RAW image data.

[0048] Specifically, in step S302, the direction of the light source in step S301 is kept still, and the shooting angle of the imaging module is adjusted to form multiple angles in order to obtain test RAW image data from multiple different angles.

[0049] In the above embodiments, the same light source is photographed from multiple different angles, making the analysis results more comprehensive.

[0050] Please refer to Figure 4 This is a schematic flowchart of the image effect processing method provided in the second embodiment of the present invention. The image effect processing method provided in the second embodiment differs from the image effect processing method provided in the first embodiment in that the method for acquiring the test RAW image data in the second embodiment is different. The image effect processing method provided in the second embodiment specifically includes the following steps.

[0051] Step S401: Keep the field of view of the imaging module unchanged in the preset scene.

[0052] Step S402: Under a preset scenario, control the light source to emit the same light and rotate the light source to change the light emission direction of the light source.

[0053] Step S403: When the light emission direction of the light source changes from one direction to another, control the imaging module to capture images to obtain the multiple test RAW image data.

[0054] In the above embodiments, the direction of the imaging module is kept unchanged, and the light emission direction of the light source is randomly changed in different directions. When the light source rotates in different directions, the imaging module captures the light source in different directions. This also realizes the examination of the imaging model's imaging problem from different angles, making the analysis results more comprehensive.

[0055] Please refer to Figure 5 This is a schematic diagram of the third sub-process of the image effect processing method provided in the first embodiment of the present invention. After obtaining the multiple test RAW image data, the test RAW image data is analyzed. The analysis process specifically includes the following steps.

[0056] Step S501: Input the multiple test RAW image data into the same ISP for simulation processing to obtain several images.

[0057] Specifically, after acquiring multiple RAW image data of the same color temperature but different directions about the light source, the multiple RAW image data are input into the ISP image processor of the same processing platform for simulation processing to obtain multiple images.

[0058] Step S502: Analyze whether the color effect of the plurality of images meets the preset effect.

[0059] Specifically, the imaging effect of the multiple images is analyzed to determine whether the imaging effect meets the preset effect.

[0060] Step S503: If the color effect of the plurality of images does not meet the preset effect, it is determined that the reason for the poor image effect is the lens in the imaging module.

[0061] Understandably, the color temperature includes warm and cool tones. Warm tones lean towards reddish-yellow, while cool tones lean towards cyan-blue. The higher the color temperature, the cooler the color emitted by the light source; the lower the color temperature, the warmer the color emitted by the light source. In this embodiment, we selected candlelight (1800-2000k) as the reference. Observation shows that candlelight has a warm color temperature, leaning towards yellow. When the lens captures light sources of the same color temperature from different directions, if the lens performance is good, the generated image will be warm and yellowish. Therefore, we can analyze the imaging effect of the generated image. If the imaging effect is not warm, it can be determined that there is a problem with the lens in the imaging module. Similarly, by inputting the same test RAW image data into other ISPs for the above test, we can find out which ISP is causing the poor image effect.

[0062] In the above embodiments, multiple sets of test RAW image data are input into the same ISP for simulation processing to obtain several images. By comparing the imaging effects of several images, it is verified whether the cause of poor image effect comes from the lens problem in the imaging module. If the image effect presented in the several images does not meet the expected effect, for example, the image effect presented by the test candle light source should be warm in tone. If the image effect of one of the several images is not warm in tone, it is determined that there is a problem with the lens in the imaging module, and the real cause of poor image effect is further traced.

[0063] Please refer to Figure 6 This is a schematic diagram of the problem image cause analysis device module provided in the embodiment of the present invention. The problem image cause analysis device 100 includes: an acquisition unit 101, a conversion unit 102, an input unit 103, a comparison unit 104, a first judgment unit 105, a second judgment unit 106, an image generation unit 107, and an analysis unit 108.

[0064] Acquisition unit 101 is used to acquire RAW image data with poor image quality.

[0065] The RAW image data is image-related data obtained directly from the shooting device, without any processing other than simple magnification and analog-to-digital conversion. It includes sensor metadata, sensor size, color attributes, configuration files, and other information. In this embodiment, when the image processed by the ISP image processor does not achieve the expected effect, the RAW image data of the poorly processed image is acquired, which is the original data of the image. Understandably, the expected effect can include, but is not limited to, situations such as excessively low or high resolution, insufficient or insufficient exposure, excessive sharpening, and the presence of artifacts in the image.

[0066] The conversion unit 102 is used to convert the RAW image data into multiple RAW image data in different formats.

[0067] Poor image quality can be caused by a problem with the ISP used to process the RAW image data, or by a problem with the RAW image data itself. To quickly determine whether the ISP is the cause of the poor image quality, the RAW image data can be processed using one or more other ISPs. Since multiple different ISPs have encountered problems processing the same RAW image data, the probability that the RAW image data itself is faulty is quite high. Therefore, in this embodiment, it is necessary to process the RAW image data using an additional ISP. Preferably, the additional ISP uses a processing platform with a different format supported by the ISP that generated the problematic image.

[0068] In order for RAW image data to be recognized or supported by other ISPs, the RAW image data needs to be converted in format. Understandably, the format conversion of the RAW image data can be achieved using existing conversion tools, which will not be elaborated here.

[0069] The input unit 103 is used to input the multiple RAW image data into multiple different processing platforms one by one to perform ISP simulation processing to obtain several images. Each processing platform supports a RAW image data format.

[0070] Specifically, after RAW image data is converted into multiple RAW image data supported by multiple different ISPs, the multiple RAW image data are respectively input into multiple different ISPs for simulation processing to obtain multiple images. Understandably, each ISP supports one or more different formats of RAW image data.

[0071] The comparison unit 104 is used to compare whether the effects of the plurality of images are the same.

[0072] After RAW image data is processed by the ISP simulation of different processing platforms, multiple images corresponding to the processing platforms are obtained. At this time, the imaging effect of multiple images is compared. In this embodiment, the effect can be compared from multiple aspects such as the exposure, sharpness, color difference, image clarity, color, and illumination uniformity of the image. Understandably, the ISPs of the different processing platforms are ISPs from different manufacturers, such as Fujifilm, Canon, Kodak, and Nikon.

[0073] The first judgment unit 105 is used to determine that if the effects of the plurality of images are the same, the poor image effect is caused by the RAW image data.

[0074] Specifically, if problems occur when processing the same RAW image data using multiple different ISPs, it indicates a high probability that the RAW image data itself is faulty. In step S104, when comparing the imaging effects of the generated images from multiple angles, if the imaging effects of each image are consistent, it indicates that the cause of the image problem is the RAW image data. In this case, it can be determined that the problem lies with the RAW image data. In some feasible embodiments, professional image analysis software can be used to analyze the effects of images output by different ISPs and print out an analysis report to help staff better understand the true cause of the image problem.

[0075] The second judgment unit 106 is used to determine that if the effects of the several images are different, the poor image effect is caused by the ISP of the processing platform.

[0076] Specifically, if the image effects output by ISP image processors of different processing platforms are inconsistent, it is highly likely that the poor image effect is caused by the ISP image processor. In some feasible embodiments, the imaging effect can be compared from multiple angles of the image. However, when comparing the effects, multiple images are compared from one angle in turn until an image with different effects at the same angle is found. Based on the image, the corresponding processing platform is found, thereby finding the ISP that is causing the poor image effect.

[0077] The image generation unit 107 is used to capture multiple test RAW image data from different angles under the same color temperature conditions using the imaging module that acquires the RAW image data. The imaging module includes an imaging sensor and a lens.

[0078] Specifically, the same color temperature is a preset color temperature, such as LED lamps, halogen lamps, fluorescent lamps, and incandescent lamps. The imaging model captures multiple test RAW image data from light sources of the same color temperature but in different directions. Understandably, there are multiple imaging modules, and each imaging module includes an imaging sensor and a lens.

[0079] The analysis unit 108 is used to analyze the multiple test RAW image data to determine whether the poor image quality is caused by the lens or the imaging sensor in the imaging module.

[0080] Specifically, the analysis of multiple test RAW image data revealed the true causes of poor image quality, with problematic components including the lens and imaging sensor.

[0081] Please refer to Figure 7 This is a schematic diagram of the image generation unit in the problem image cause analysis device provided in the embodiment of the present invention. The image generation unit 107 further includes: a control unit 1071 and an adjustment unit 1072.

[0082] The control unit 1071 is used to control the light source to emit the same light under a preset scene.

[0083] The adjustment unit 1072 is used to sequentially adjust the imaging module to different viewing angles under the preset scene to obtain multiple test RAW image data.

[0084] In the above embodiments, to quickly determine whether the poor image quality is caused by the ISP, one or more ISPs are used to process the RAW image data of the problem image to obtain several images. Then, the image quality output by different ISPs is compared. If the image quality output by each different ISP is consistent, it indicates that the poor image quality is very likely not caused by the ISP. At this point, the target is narrowed down to the RAW image data. Furthermore, the imaging module that acquires the RAW image data is analyzed to determine whether the problem lies with the lens or the imaging sensor. This solution effectively traces the true cause of the poor image quality without requiring additional specialized testing equipment to detect problems with the ISP and the raw image data, thus saving costs.

[0085] Please refer to Figure 8 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of the present invention. The computer device 30 specifically includes a memory 302 and a processor 301. The memory 302 is used to store program instructions, and the processor 301 is used to execute the program instructions to implement the aforementioned image effect processing method.

[0086] In some embodiments, processor 301 may be a central processing unit (CPU), controller, microcontroller, microprocessor or other data processing chip, used to run program instructions stored in memory 302.

[0087] The memory 302 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 302 can be an internal storage unit of a computer device, such as a hard disk. In other embodiments, the memory 302 can be an external storage device of a computer device, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, FlashCard, etc., provided on the computer device. Furthermore, the memory 302 can include both internal and external storage units of the computer device. The memory 302 can be used not only to store application software and various types of data installed on the computer device, such as code implementing image processing methods, but also to temporarily store data that has been output or will be output.

[0088] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0089] The above-listed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. An image effect processing method, wherein the image is an image processed by ISP, characterized in that, The image effect processing method includes: Acquire RAW image data with poor image quality, wherein the RAW image data with poor image quality is the corresponding RAW image data obtained when the image does not achieve the expected effect after ISP processing; The RAW image data is converted to different formats to obtain multiple RAW image data files; The multiple RAW image data are input one-to-one into various different processing platforms for ISP simulation processing to obtain several images. Each processing platform supports a different RAW image data format. The formats supported by the various processing platforms are different from the formats supported by the image processing platform corresponding to the ISP that produced the RAW image data with poor image quality. Compare whether the effects of the aforementioned images are the same; If the effects of the aforementioned images are the same, it is determined that the poor image quality is caused by the RAW image data. If the effects of the various images are different, it is determined that the poor image effect is caused by the ISP of the processing platform.

2. The image effect processing method as described in claim 1, characterized in that, After determining that the poor image quality is caused by RAW image data, the image quality processing method further includes: Multiple test RAW image data are obtained by using an imaging module that acquires the RAW image data from different angles under the same color temperature conditions. The imaging module includes an imaging sensor and a lens. Analysis of the multiple test RAW image data revealed whether the poor image quality was caused by the lens or the imaging sensor in the imaging module.

3. The image effect processing method as described in claim 2, characterized in that, The imaging module that acquires the RAW image data captures multiple test RAW image data sets from different angles under the same color temperature conditions, specifically including: Control the light sources to emit the same light in a preset scene; In the preset scenario, the imaging module is sequentially adjusted to different viewing angles before shooting to obtain the multiple sets of test RAW image data.

4. The image effect processing method as described in claim 3, characterized in that, The process of acquiring multiple test RAW image data sets by using an imaging module that acquires the RAW image data to capture images from different angles under the same color temperature also includes: The imaging module maintains a constant field of view in the preset scene. In a preset scenario, control the light source to emit the same light and rotate the light source to change the light emission direction of the light source; When the light source changes its emission direction from one direction to another, the imaging module is controlled to capture images to obtain multiple sets of test RAW image data.

5. The image effect processing method as described in claim 2, characterized in that, Analysis of the multiple test RAW image data revealed whether the poor image quality was caused by the lens or the imaging sensor in the imaging module. Specifically, this included: The multiple test RAW image data are input into the same processing platform for ISP simulation processing to obtain several images; Analyze whether the color effects of the aforementioned images meet the preset requirements; If the color effect of the aforementioned images does not meet the preset effect, it is determined that the reason for the poor image effect lies in the lens of the imaging module.

6. An image effect processing apparatus, characterized in that, The image effect processing device includes: The acquisition unit is used to acquire RAW image data with poor image quality. The RAW image data with poor image quality is the corresponding RAW image data acquired when the image does not achieve the expected effect after ISP processing. A conversion unit is used to convert the RAW image data into multiple RAW image data in different formats. The input unit is used to input the multiple RAW image data into multiple different processing platforms one by one for ISP simulation processing to obtain several images. Each processing platform supports a RAW image data format. The formats supported by the multiple different processing platforms are different from the formats supported by the image processing platform corresponding to the ISP that produces the RAW image data with poor image quality. A comparison unit is used to compare whether the effects of the plurality of images are the same; The first judgment unit is used to determine that if the effects of the plurality of images are the same, the poor image effect is caused by the RAW image data. The second judgment unit is used to determine that if the effects of the several images are different, the poor image effect is caused by the ISP of the processing platform.

7. The image effect processing apparatus as described in claim 6, characterized in that, Also includes: An image generation unit is used to capture multiple test RAW image data from different angles under the same color temperature conditions using an imaging module that acquires the RAW image data. The imaging module includes an imaging sensor and a lens. The analysis unit is used to analyze the multiple test RAW image data to determine whether the poor image quality is caused by the lens or the imaging sensor in the imaging module.

8. The image effect processing apparatus as described in claim 7, characterized in that, The image generation unit further includes: The control unit is used to control the light source to emit the same light under a preset scene. The adjustment unit is used to sequentially adjust the imaging module to different viewing angles under the preset scene before taking pictures to obtain the multiple test RAW image data.

9. A computer device, comprising: Memory, used to store executable programs in a computer. A processor for executing the computer-executable program to implement the image effect processing method as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the image effect processing method as described in any one of claims 1-5.

Images