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

Abstract

According to the image data processing method and device, the electronic equipment, the storage medium and the chip provided by the invention, the configuration parameters of all the to-be-compressed curves are obtained before electrification, each to-be-compressed curve comprises at least two groups of configuration parameters, and according to the similar difference values of the corresponding configuration parameters between the adjacent pixels, the to-be-compressed curves are obtained; at least two sets of configuration parameters of all the to-be-compressed curves are compressed based on the image signal processor to obtain compressed curve configuration parameters, the compressed curve configuration parameters are decompressed based on the image signal processor after power-on to obtain decompressed curve configuration parameters, and the decompressed curve configuration parameters are sent to the image signal processor. And configuring the decompressed curve configuration parameters into the corresponding registers. The existing hardware resources (compression and decompression) of the image signal processor are multiplexed, the configuration parameters of all to-be-compressed curves are compressed, the configuration parameters are configured to a register of the image signal processor on the basis of the decompressed curve configuration parameters after power-on, and the occupation of the DDR storage space by the uncompressed curve configuration parameters is reduced.

Description

Technical Field

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

[0002] In order to meet users' high demands for images, when processing images, it is necessary to truly restore the objective visual effects of the images and reduce the cost of using chips when the terminal processes images.

[0003] At present, in order to achieve the above two goals, images are often processed through image processing algorithms. However, in the face of light sources, illumination and complex scenes in different time periods, more complex algorithms are required. This also means that adaptive configuration is required based on environmental parameters such as different scene complexities and lighting conditions, and precise algorithm parameters are matched based on the current ambient light and scene complexity to obtain high-quality images.

[0004] To adapt to different light sources, lighting conditions, and scenes, and adjust image quality and noise reduction, the Image Signal Processor (ISP) requires pre-calibrated configuration parameters for various algorithms under various lighting conditions. These configuration parameters are stored in a memory unit (Double Data Rate SDRAM, DDR). During image processing, the Central Processing Unit (CPU) reads the configuration parameters from the DDR and allocates them to the corresponding registers in the ISP's functional modules. Because the configuration parameters are large in size, storing them in the DDR wastes memory resources. Summary of the Invention

[0005] The present disclosure provides an image data processing method and device, electronic device, storage medium and chip, which are mainly intended to solve the problem of large storage resources occupied by configuration parameters of multiple algorithms in DDR.

[0006] According to a first aspect of the present disclosure, a method for processing image data is provided, comprising:

[0007] Before powering on, obtaining configuration parameters of all curves to be compressed, wherein each curve to be compressed includes at least two sets of configuration parameters;

[0008] Compressing at least two groups of configuration parameters of all the to-be-compressed curves based on an image signal processor according to similarity differences of configuration parameters corresponding to adjacent pixels, to obtain compressed curve configuration parameters;

[0009] After power-on, decompressing the compressed curve configuration parameters based on the image signal processor to obtain decompressed curve configuration parameters;

[0010] The decompressed curve configuration parameters are configured into registers corresponding to the image signal processor.

[0011] In some embodiments of the present disclosure, compressing at least two groups of configuration parameters of all the to-be-compressed curves based on the image signal processor according to similarity differences of configuration parameters corresponding to adjacent pixels to obtain compressed curve configuration parameters includes:

[0012] Sending a compression instruction to the image signal processor, and compressing at least two groups of configuration parameters of all the curves to be compressed based on a compression module in the image signal processor to obtain the compressed curve configuration parameters;

[0013] The compressed curve configuration parameters are stored in a temporary storage space of the image signal processor.

[0014] In some embodiments of the present disclosure, compressing at least two groups of configuration parameters of all the curves to be compressed based on a compression module in the image signal processor to obtain the compressed curve configuration parameters includes:

[0015] According to the pre-calibrated configuration parameters, the configuration parameters corresponding to each two adjacent pixels are determined;

[0016] Calculating the difference between the configuration parameters corresponding to two adjacent pixels in each of the two groups of configuration parameters as the similarity difference;

[0017] The configuration parameters corresponding to each of the two adjacent pixels are compressed based on the similarity difference to obtain the compressed curve configuration parameters.

[0018] In some embodiments of the present disclosure, after powering on, decompressing the compressed curve configuration parameters based on the image signal processor to obtain the decompressed curve configuration parameters includes:

[0019] Reading the compressed curve configuration parameters from the first temporary storage space of the image signal processor, and moving the read compressed curve configuration parameters to the memory storage space;

[0020] A decompression instruction is sent to the image signal processor, and based on a decompression module in the image signal processor, the compressed curve configuration parameters are decompressed by the image signal processor to obtain decompressed curve configuration parameters.

[0021] In some embodiments of the present disclosure, the method further includes:

[0022] The decompressed curve configuration parameters are stored in a second temporary storage space of the image signal processor.

[0023] In some embodiments of the present disclosure, configuring the decompressed curve configuration parameters into a register corresponding to the image signal processor includes:

[0024] In response to a decompression interrupt sent by the image signal processor, reading the decompressed curve configuration parameters from the second temporary storage space;

[0025] The decompressed curve configuration parameters are used to configure the registers corresponding to the respective curves.

[0026] According to a second aspect of the present disclosure, there is provided an apparatus for processing image data, comprising:

[0027] An acquisition unit, configured to acquire configuration parameters of all curves to be compressed before power-on, wherein each curve to be compressed includes at least two groups of configuration parameters;

[0028] a compression unit, configured to compress at least two groups of configuration parameters of all the to-be-compressed curves based on an image signal processor according to similarity differences of configuration parameters corresponding to adjacent pixels, to obtain compressed curve configuration parameters;

[0029] a decompression unit, configured to, after power-on, decompress the compressed curve configuration parameters based on the image signal processor to obtain decompressed curve configuration parameters;

[0030] A configuration unit is used to configure the decompressed curve configuration parameters into a register corresponding to the image signal processor.

[0031] In some embodiments of the present disclosure, the compression unit includes:

[0032] A sending module, configured to send a compression instruction to the image signal processor;

[0033] a compression module, configured to compress at least two groups of configuration parameters of all the curves to be compressed based on the compression module in the image signal processor, to obtain the compressed curve configuration parameters;

[0034] A storage module is used to store the compressed curve configuration parameters in a temporary storage space of the image signal processor.

[0035] In some embodiments of the present disclosure, the compression module is further configured to:

[0036] According to the pre-calibrated configuration parameters, the configuration parameters corresponding to each two adjacent pixels are determined;

[0037] Calculating the difference between the configuration parameters corresponding to two adjacent pixels in each of the two groups of configuration parameters as the similarity difference;

[0038] The configuration parameters corresponding to each of the two adjacent pixels are compressed based on the similarity difference to obtain the compressed curve configuration parameters.

[0039] In some embodiments of the present disclosure, the decompression unit includes:

[0040] a reading module, configured to read the compressed curve configuration parameters from the first temporary storage space of the image signal processor, and transfer the read compressed curve configuration parameters to the memory storage space;

[0041] A sending module, configured to send a decompression instruction to the image signal processor;

[0042] A decompression module is configured to decompress the compressed curve configuration parameters based on the image signal processor based on the decompression module in the image signal processor to obtain decompressed curve configuration parameters.

[0043] In some embodiments of the present disclosure, the apparatus further comprises:

[0044] A storage unit is used to store the decompressed curve configuration parameters in a second temporary storage space of the image signal processor.

[0045] In some embodiments of the present disclosure, the configuration unit includes:

[0046] a reading module, configured to read the decompressed curve configuration parameters from the second temporary storage space in response to a decompression interrupt sent by the image signal processor;

[0047] The configuration module is used to use the decompressed curve configuration parameters to configure the registers corresponding to the respective curves.

[0048] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0049] at least one processor; and

[0050] a memory communicatively connected to the at least one processor; wherein,

[0051] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0052] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0053] According to a fifth aspect of the present disclosure, a chip is provided, comprising one or more interface circuits and one or more processors; the interface circuits are configured to receive signals and send the signals to the processors, wherein the signals include computer instructions; when the processors execute the computer instructions, the chip executes the method described in the first aspect.

[0054] According to a sixth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0055] The image data processing method and device, electronic device, storage medium, and chip provided by the present disclosure obtain configuration parameters of all curves to be compressed before power is turned on, wherein each curve to be compressed includes at least two sets of configuration parameters. According to the similarity difference between the configuration parameters corresponding to adjacent pixels, the at least two sets of configuration parameters of all curves to be compressed are compressed based on the image signal processor to obtain compressed curve configuration parameters. After power is turned on, the compressed curve configuration parameters are decompressed based on the image signal processor to obtain decompressed curve configuration parameters, and the decompressed curve configuration parameters are configured into corresponding registers. The embodiment of the present disclosure reuses the existing hardware resources (compression and decompression functions) of the image signal processor, first compresses at least two sets of configuration parameters of all curves to be compressed, and after power is turned on, the decompressed curve configuration parameters are configured into the corresponding registers of the image signal processor, thereby reducing the DDR storage space occupied by the uncompressed curve configuration parameters.

[0056] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0058] Figure 1 A flowchart of a method for processing image data provided by an embodiment of the present disclosure;

[0059] Figure 2 A flowchart of another method for processing image data provided by an embodiment of the present disclosure;

[0060] Figure 3 A schematic diagram of an image data processing system provided in an embodiment of the present disclosure;

[0061] Figure 4 A flowchart of another method for processing image data provided by an embodiment of the present disclosure;

[0062] Figure 5 A flowchart of another method for processing image data provided by an embodiment of the present disclosure;

[0063] Figure 6 A flowchart of another method for processing image data provided by an embodiment of the present disclosure;

[0064] Figure 7 A schematic structural diagram of an image data processing device provided by an embodiment of the present disclosure;

[0065] Figure 8 A schematic structural diagram of another image data processing device provided by an embodiment of the present disclosure;

[0066] Figure 9 A schematic block diagram of an example electronic device provided for an embodiment of the present disclosure;

[0067] Figure 10 A schematic block diagram of a chip provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0068] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0069] The following describes the image data processing method and apparatus, electronic device, storage medium, and chip according to the embodiments of the present disclosure with reference to the accompanying drawings.

[0070] Figure 1 A flowchart of an image data processing method provided by an embodiment of the present disclosure.

[0071] like Figure 1 As shown, the method comprises the following steps:

[0072] Step 101 : Before powering on, obtain configuration parameters of all curves to be compressed, wherein each curve to be compressed includes at least two groups of configuration parameters.

[0073] The ISP is configured with a variety of continuous and smooth configuration curve parameters, such as the GAMMA curve, lens distortion correction curve, noise model curve, adaptive motion weight configuration curve, or image processing chips and other configuration parameters corresponding to the configuration curve. The curve parameters configured in the ISP are not limited. The subsequent embodiments will use the GAMMA curve as an example. It should be noted that this description is not intended to be limiting. The ISP only contains the GAMMA curve.

[0074] See also Figure 2 Taking the GAMMA curve as an example, a GAMMA curve includes N parameters. Each set of configuration parameters varies based on the imaging light source, illumination, scene, and other factors. The disclosed embodiments do not limit the number of configuration parameters corresponding to each curve. These curve parameters and their configuration parameters are calculated in advance. When processing images based on the ISP, the configured curve configuration parameters can be used to complete image processing.

[0075] Before the ISP is powered on, the CPU obtains all configuration parameters of the compression curve required by the ISP.

[0076] Step 102 : Compress at least two groups of configuration parameters of all the curves to be compressed based on an image signal processor according to similarity differences of configuration parameters corresponding to adjacent pixels, to obtain compressed curve configuration parameters.

[0077] As explained in step 101, the configuration parameters of the curve are all pre-calculated, that is, the specific parameter values are predetermined. When performing compression of the configuration parameters, compression can be performed based on the correlation between the configuration parameters of the smooth curve. The correlation means that there is a strong correlation between adjacent pixels, and the corresponding two configuration parameters also have a correlation. For example, please continue to refer to Figure 2 , the similarity difference between the parameter values corresponding to parameter 1 and parameter 2 is small, indicating that the similarity between the two pixels is large. Therefore, when compressing, the correlation information (similarity information) between parameter 1 and parameter 2 can be removed to achieve the purpose of compression, reduce the data volume of these parameters, and thus reduce the DDR space required to store the parameters and the bandwidth for reading the DDR parameters.

[0078] During compression, the CPU invokes existing hardware resources (compression modules, such as the IFBC module) within the image signal processor (ISP) to compress the configuration parameters. Compression can employ, but is not limited to, the JPEG-lossless algorithm or any other lossless compression method, and the present disclosure does not further elaborate on this aspect.

[0079] Step 103 : After power-on, decompress the compressed curve configuration parameters based on the image signal processor to obtain decompressed curve configuration parameters.

[0080] After the system is powered on, the system direct memory access (DMA) moves the compressed curve configuration parameters obtained in step 102 to the DDR. The CPU calls the decompression module in the ISP (such as the IFBD module) to move the compressed curve configuration parameters taken out from the DDR to the IFBD module for decompression to obtain the decompressed curve configuration parameters.

[0081] Step 104: configure the decompressed curve configuration parameters into the corresponding register of the image signal processor.

[0082] After the decompression module completes decompression, it sends a notification message to the CPU. The CPU then reads the decompressed curve configuration parameters from the ISP and configures the registers corresponding to each curve in the ISP. For example, the configuration parameters corresponding to the gamma curve are configured in the gamma register, and the configuration parameters corresponding to the lens distortion correction curve are configured in the lens distortion correction curve register, and so on.

[0083] After the register configuration is completed, the image is processed by adjusting the image quality, reducing noise, etc. to obtain an image with better image quality.

[0084] The image data processing method provided by the present disclosure obtains configuration parameters of all curves to be compressed before power is applied, wherein each curve to be compressed includes at least two sets of configuration parameters. Based on the similarity difference between the configuration parameters corresponding to adjacent pixels, the at least two sets of configuration parameters of all curves to be compressed are compressed based on the image signal processor to obtain compressed curve configuration parameters. After power is applied, the compressed curve configuration parameters are decompressed based on the image signal processor to obtain decompressed curve configuration parameters, and the decompressed curve configuration parameters are configured into corresponding registers. The embodiment of the present disclosure reuses the existing hardware resources (compression and decompression functions) of the image signal processor, first compressing the at least two sets of configuration parameters of all curves to be compressed. After power is applied, the decompressed curve configuration parameters are configured into the corresponding registers of the image signal processor, thereby reducing the DDR memory space occupied by the uncompressed curve configuration parameters.

[0085] like Figure 3 As shown, Figure 3 This is a schematic diagram of an image data processing system provided by an embodiment of the present disclosure. Figures 4 to 6 Provide detailed explanation.

[0086] Figure 4The following further shows a flow chart of a method for processing image data proposed in the present disclosure. Figure 1 The embodiment shown further explains step 102. Figure 4 The following steps may be included:

[0087] Step 201 : Send a compression instruction to the image signal processor, and compress at least two groups of configuration parameters of all the curves to be compressed respectively based on a compression module in the image signal processor to obtain the compressed curve configuration parameters.

[0088] Please continue reading Figure 3 The CPU sends a compression instruction to the ISP, and the ISP compression module performs lossless compression on all curve configuration parameters to obtain compressed curve configuration parameters. When performing compression, the image lossless compression module (IFBC) or IFBC algorithm in the ISP is used, which is not limited in the embodiment of the present disclosure.

[0089] Taking the compression module as an example, compression can be implemented in the following ways, but not limited to:

[0090] According to the pre-calibrated configuration parameters, the configuration parameters corresponding to each of two adjacent pixels are determined;

[0091] Calculating the difference between the configuration parameters corresponding to two adjacent pixels in each of the two groups of configuration parameters as the similarity difference;

[0092] The configuration parameters corresponding to each of the two adjacent pixels are compressed based on the similarity difference to obtain the compressed curve configuration parameters.

[0093] The above embodiments have explained that the configuration parameters of the curve are all pre-calculated, that is, the specific parameter values are predetermined. When the compression module performs compression of the configuration parameters, compression can be performed based on the correlation between the configuration parameters of the smooth curve. The correlation means that there is a strong correlation between adjacent pixels, and the corresponding two configuration parameters also have a correlation. For example, please continue to refer to Figure 2 , the similarity difference between the parameter values corresponding to parameter 1 and parameter 2 is small, indicating that the similarity between the two pixels is large. Therefore, when compressing, the correlation information (similarity information) between parameter 1 and parameter 2 can be removed to achieve the purpose of compression, reduce the data volume of these parameters, and thus reduce the DDR space required to store the parameters and the bandwidth for reading the DDR parameters.

[0094] For example, if the value of parameter 1 is 100, the value of parameter 2 is 102, and the value of parameter 3 is 103, then the compressed parameter 1, parameter 2, and parameter 3 are 100, +2, +1, etc. respectively. It should be noted that the above examples are only illustrative examples and are not limitations on specific values.

[0095] In some embodiments, compression is performed based on the size of the similarity difference. The larger the similarity difference, the smaller the similarity of the corresponding pixels. Therefore, when compressing, parameters with relatively large similarity differences cannot be compressed to avoid affecting the quality of image processing by the ISP. In practical applications, a specific threshold or numerical range of similarity differences can be set. When the similarity difference between two parameters is less than the threshold or is within the numerical range, compression of the two parameters is performed. The specific threshold or numerical range can be set based on the hardware processing resources. The embodiment of the present disclosure does not limit the size of the threshold or numerical range of the similarity difference.

[0096] In actual applications, the CPU organizes the various calibrated curve parameters into image pixel format files and passes them to the image lossless compression hardware unit (IFBC) in the ISP, or uses a lossless image compression algorithm corresponding to the lossless decompression algorithm in the ISP for software compression.

[0097] Step 202: Store the compressed curve configuration parameters in a first temporary storage space of the image signal processor.

[0098] After the compressed curve configuration parameters are obtained by the compression module, they are built into the ISP firmware and stored in the first temporary storage space (such as flash memory space). The embodiment of the present disclosure does not limit the specific location where the compressed curve configuration parameters are stored.

[0099] Figure 5 The following further shows a flow chart of a method for processing image data proposed in the present disclosure. Figure 1 The embodiment shown further explains step 103. Figure 5 The following steps may be included:

[0100] Step 301: Read the compressed curve configuration parameters from the first temporary storage space of the image signal processor, and move the read compressed curve configuration parameters to the memory storage space.

[0101] Please continue reading Figure 3 After the system is powered on, the system DMA moves the compressed curve configuration parameters in the ISP firmware (such as the flash memory space) to the DDR for storage.

[0102] Step 302: Send a decompression instruction to the image signal processor, and decompress the compressed curve configuration parameters based on the image signal processor using a decompression module in the image signal processor to obtain decompressed curve configuration parameters.

[0103] The CPU calls the IFBD (image lossless decompression hardware unit) in the ISP, and sends the compressed curve configuration read from the DDR to the IFBD module for decompression to obtain the decompressed curve configuration parameters. The decompressed curve configuration parameters are consistent with the configuration parameters before the CPU calls the compression module of the ISP.

[0104] Step 303: Store the decompressed curve configuration parameters in a second temporary storage space of the image signal processor.

[0105] After being decompressed by the decompression module, the decompressed curve configuration parameters are stored in a second temporary storage space of the ISP, such as a public memory unit (cache), waiting to be configured to the register.

[0106] Figure 6 The following further shows a flow chart of a method for processing image data proposed in the present disclosure. Figure 1 The embodiment shown further explains step 103. Figure 6 The following steps may be included:

[0107] Step 401: In response to a decompression interrupt sent by the image signal processor, read the decompressed curve configuration parameters from the second temporary storage space.

[0108] Step 402: Use the decompressed curve configuration parameters to configure registers corresponding to the respective curves.

[0109] Please continue reading Figure 3 After the CPU receives the interruption of the decompression module, it calls the configuration register DMA in the ISP to configure the compressed curve configuration parameters stored in the memory unit in the ISP to the corresponding registers of the functional module; for example, it configures the gamma curve parameters to the gamma register, etc.

[0110] The embodiments of the present disclosure can achieve the following beneficial effects:

[0111] 1. Using lossless image compression algorithm to compress curve configuration parameters can greatly reduce the amount of data of curve configuration parameters in DDM;

[0112] 2. Reuse the ISP's existing lossless image compression unit and decompression hardware unit without adding any new system resources.

[0113] Corresponding to the above-mentioned image data processing method, the present invention also provides an image data processing device. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment and will not be further described in the present invention.

[0114] Figure 7 A schematic diagram of the structure of an image data processing device provided by an embodiment of the present disclosure is shown in FIG. Figure 7 As shown, including:

[0115] An acquisition unit 51 is configured to acquire configuration parameters of all curves to be compressed before power is turned on, wherein each curve to be compressed includes at least two groups of configuration parameters;

[0116] a compression unit 52 configured to compress at least two groups of configuration parameters of all the to-be-compressed curves based on an image signal processor according to similarity differences of configuration parameters corresponding to adjacent pixels, to obtain compressed curve configuration parameters;

[0117] a decompression unit 53 configured to, after power-on, decompress the compressed curve configuration parameters based on the image signal processor to obtain decompressed curve configuration parameters;

[0118] The configuration unit 54 is configured to configure the decompressed curve configuration parameters into a register corresponding to the image signal processor.

[0119] The image data processing device provided by the present disclosure obtains configuration parameters of all curves to be compressed before power is applied, wherein each curve to be compressed includes at least two sets of configuration parameters. Based on the similarity difference between the configuration parameters corresponding to adjacent pixels, the image signal processor compresses the at least two sets of configuration parameters for all curves to be compressed, respectively, to obtain compressed curve configuration parameters. After power is applied, the image signal processor decompresses the compressed curve configuration parameters to obtain decompressed curve configuration parameters, and configures the decompressed curve configuration parameters into corresponding registers. The embodiment of the present disclosure reuses the existing hardware resources (compression and decompression functions) of the image signal processor, first compressing the at least two sets of configuration parameters for all curves to be compressed. After power is applied, the decompressed curve configuration parameters are then configured into corresponding registers of the image signal processor, thereby reducing the DDR memory space occupied by the uncompressed curve configuration parameters.

[0120] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 8 As shown, the compression unit 52 includes:

[0121] A sending module 521 is configured to send a compression instruction to the image signal processor;

[0122] A compression module 522 is configured to compress at least two groups of configuration parameters of all the curves to be compressed based on the compression module in the image signal processor to obtain the compressed curve configuration parameters;

[0123] The storage module 523 is configured to store the compressed curve configuration parameters in a temporary storage space of the image signal processor.

[0124] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 8 As shown, the compression module 522 is further configured to:

[0125] According to the pre-calibrated configuration parameters, the configuration parameters corresponding to each two adjacent pixels are determined;

[0126] Calculating the difference between the configuration parameters corresponding to two adjacent pixels in each of the two groups of configuration parameters as the similarity difference;

[0127] The configuration parameters corresponding to each of the two adjacent pixels are compressed based on the similarity difference to obtain the compressed curve configuration parameters.

[0128] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 8 As shown, the decompression unit 53 includes:

[0129] A reading module 531 is configured to read the compressed curve configuration parameters from the first temporary storage space of the image signal processor and transfer the read compressed curve configuration parameters to the memory storage space;

[0130] A sending module 532, configured to send a decompression instruction to the image signal processor;

[0131] The decompression module 533 is configured to decompress the compressed curve configuration parameters based on the image signal processor using a decompression module in the image signal processor to obtain decompressed curve configuration parameters.

[0132] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 8 As shown, the device also includes:

[0133] The storage unit 55 is configured to store the decompressed curve configuration parameters in a second temporary storage space of the image signal processor.

[0134] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 8 As shown, the configuration unit 54 includes:

[0135] a reading module 541, configured to read the decompressed curve configuration parameters from the second temporary storage space in response to a decompression interrupt sent by the image signal processor;

[0136] The configuration module 542 is configured to use the decompressed curve configuration parameters to configure registers corresponding to respective curves.

[0137] It should be noted that the above explanation of the method embodiment is also applicable to the device of the embodiment of the present disclosure, and the principles are the same, which is no longer limited in the embodiment of the present disclosure.

[0138] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0139] Figure 9 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided as examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0140] like Figure 9 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 602 or a computer program loaded from a storage unit 608 into a RAM (Random Access Memory) 603. Various programs and data required for the operation of the device 600 can also be stored in the RAM 603. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An I / O (Input / Output) interface 605 is also connected to the bus 604.

[0141] Various components in device 600 are connected to I / O interface 605, including an input unit 606, such as a keyboard, mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a magnetic disk, optical disk, etc.; and a communication unit 609, such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows device 600 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0142] The computing unit 601 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), various specialized AI (Artificial Intelligence) computing chips, various computing units that run machine learning model algorithms, a DSP (Digital Signal Processor), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as the image data processing method. For example, in some embodiments, the image data processing method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the method described above can be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to execute the aforementioned image data processing method in any other appropriate manner (for example, by means of firmware).

[0143] For electronic devices that can be chips or chip systems, see Figure 10 Schematic diagram of the chip structure shown. Figure 10 The chip shown includes a processor 701 and an interface 702. There may be one or more processors 701 and there may be more than one interface 702.

[0144] Optionally, the chip further includes a memory 703, which is used to store necessary computer programs and data.

[0145] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System on Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0146] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0147] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0148] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0149] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0150] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact via a communication network. This client-server relationship is established by computer programs running on the respective computers, establishing a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host, a host product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosts and VPS services ("Virtual Private Servers" or simply "VPS"). The server may also be a server in a distributed system or a server integrated with blockchain.

[0151] It's important to note that artificial intelligence (AI) is the study of how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). This encompasses both hardware and software technologies. AI hardware technologies generally include sensors, specialized AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily encompass computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graphs.

[0152] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not limited herein.

[0153] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A method for processing image data, characterized in that: include: Before powering on, obtaining configuration parameters of all curves to be compressed, wherein each curve to be compressed includes at least two sets of configuration parameters; Compressing at least two groups of configuration parameters of all the to-be-compressed curves based on an image signal processor according to similarity differences of configuration parameters corresponding to adjacent pixels, to obtain compressed curve configuration parameters; After power-on, decompressing the compressed curve configuration parameters based on the image signal processor to obtain decompressed curve configuration parameters; The decompressed curve configuration parameters are configured into registers corresponding to the image signal processor.

2. The method according to claim 1, characterized in that The step of compressing at least two groups of configuration parameters of all the curves to be compressed based on the image signal processor according to the similarity difference of the configuration parameters corresponding to adjacent pixels to obtain the compressed curve configuration parameters includes: Sending a compression instruction to the image signal processor, and compressing at least two groups of configuration parameters of all the curves to be compressed based on a compression module in the image signal processor to obtain the compressed curve configuration parameters; The compressed curve configuration parameters are stored in a first temporary storage space of the image signal processor.

3. The method according to claim 2, characterized in that The compression module in the image signal processor compresses at least two groups of configuration parameters of all the curves to be compressed respectively to obtain the compressed curve configuration parameters, which includes: According to the pre-calibrated configuration parameters, the configuration parameters corresponding to each of two adjacent pixels are determined; Calculating the difference between the configuration parameters corresponding to two adjacent pixels in each of the two groups of configuration parameters as the similarity difference; The configuration parameters corresponding to each of the two adjacent pixels are compressed based on the similarity difference to obtain the compressed curve configuration parameters.

4. The method according to claim 2, characterized in that After powering on, decompressing the compressed curve configuration parameters based on the image signal processor to obtain the decompressed curve configuration parameters includes: Reading the compressed curve configuration parameters from the first temporary storage space of the image signal processor, and moving the read compressed curve configuration parameters to the memory storage space; A decompression instruction is sent to the image signal processor, and based on a decompression module in the image signal processor, the compressed curve configuration parameters are decompressed by the image signal processor to obtain decompressed curve configuration parameters.

5. The method according to claim 4, characterized in that The method further comprises: The decompressed curve configuration parameters are stored in a second temporary storage space of the image signal processor.

6. The method according to claim 5, characterized in that The configuring the decompressed curve configuration parameters into a register corresponding to the image signal processor includes: In response to a decompression interrupt sent by the image signal processor, reading the decompressed curve configuration parameters from the second temporary storage space; The decompressed curve configuration parameters are used to configure the registers corresponding to the respective curves.

7. An image data processing device, characterized in that: include: An acquisition unit, configured to acquire configuration parameters of all curves to be compressed before power-on, wherein each curve to be compressed includes at least two groups of configuration parameters; a compression unit, configured to compress at least two groups of configuration parameters of all the to-be-compressed curves based on an image signal processor according to similarity differences of configuration parameters corresponding to adjacent pixels, to obtain compressed curve configuration parameters; a decompression unit, configured to, after power-on, decompress the compressed curve configuration parameters based on the image signal processor to obtain decompressed curve configuration parameters; A configuration unit is used to configure the decompressed curve configuration parameters into a register corresponding to the image signal processor.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

10. A chip, characterized in that: The chip comprises one or more interface circuits and one or more processors; the interface circuit is used to receive a signal and send the signal to the processor, wherein the signal includes a computer instruction; when the processor executes the computer instruction, the chip executes the method according to any one of claims 1 to 6.

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