Image data processing method, device and computer equipment in three-dimensional scanning

Abstract

The application relates to a three-dimensional scanning image data processing method, device and computer equipment, wherein the three-dimensional scanning image data processing method comprises the following steps: determining a target category to which each standard mapping table pre-stored in a calculation unit belongs; the calculation unit is pre-associated with a data compression unit used for generating an image compression file; based on a preset compression rule, an original scanning image is compressed to obtain a corresponding image compression file; the preset compression rule indicates that a mapping table of the target category is not required to be generated in the compression process; the image compression file is transmitted to the calculation unit, and the image compression file is decoded based on the standard mapping table corresponding to the image compression file. Through the application, the problem that scanning data cannot be efficiently transmitted to a calculation unit for calculation due to a great influence of color image compression data and low three-dimensional scanning efficiency is solved, and scanning data is efficiently transmitted to the calculation unit, and the three-dimensional scanning efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to image data processing methods, apparatus and computer equipment in three-dimensional scanning. Background Technology

[0002] Current 3D scanning systems typically acquire raw image data of the object being scanned and then transmit this data to a personal computer or other computing unit for data processing and subsequent matching and reconstruction operations. However, transmitting raw image data results in a large data transfer volume, impacting scanning efficiency.

[0003] To address the aforementioned issues, existing technologies pre-compress the raw image data to be transmitted before transmitting the compressed data. However, images acquired through 3D scanning typically include both black-and-white and color images. The black-and-white image is used for imaging, while the color image is used for colorizing the imaged object. After processing by existing compression algorithms, the Huffman coding information of the color image occupies a significant amount of bandwidth during data transmission, forcing a reduction in the transmission frame rate. Consequently, when applying existing compression algorithms, the compression of the color image data significantly impacts the efficiency of transmitting the scanned data to the computing unit for computation, resulting in low 3D scanning efficiency.

[0004] There is currently no effective solution to the problem that the efficiency of 3D scanning is greatly affected by the compression of color image data, making it impossible to efficiently transmit the scanned data to the computing unit for calculation, resulting in low efficiency. Summary of the Invention

[0005] This embodiment provides an image data processing method, apparatus, and computer device for three-dimensional scanning, in order to solve the problem in related technologies where the scanning data is greatly affected by the compression of color image data, making it impossible to efficiently transmit the scanning data to the computing unit for calculation, resulting in low efficiency of three-dimensional scanning.

[0006] Firstly, this embodiment provides an image data processing method for three-dimensional scanning, the method comprising:

[0007] The target category to which each standard mapping table pre-stored in the computing unit belongs is determined; the computing unit is pre-associated with a data compression unit used to generate image compressed files;

[0008] Based on preset compression rules, the original scanned image is compressed to obtain a corresponding image compressed file; the preset compression rules indicate that the compression process does not need to generate a mapping table for the target category; the image compressed file is transmitted to the computing unit, and the image compressed file is decoded based on the standard mapping table corresponding to the image compressed file.

[0009] In some embodiments, decoding the image compressed file based on the standard mapping table corresponding to the image compressed file includes:

[0010] Determine the scanning scene associated with the image compression file;

[0011] Retrieve the standard mapping table corresponding to the scanning scene from the preset decoding algorithm library;

[0012] The image compressed file is decoded based on the standard mapping table corresponding to the scanning scene.

[0013] In some embodiments, the standard mapping table includes a quantization table and / or a Huffman coding table.

[0014] In some embodiments, the compression of the original scanned image to obtain a corresponding compressed image file includes:

[0015] The original scanned image is converted into corresponding frequency domain data;

[0016] The frequency domain data is quantized.

[0017] The quantized frequency domain data is then subjected to run-length encoding and Huffman encoding to obtain the corresponding image compressed file.

[0018] In some embodiments, after quantizing the frequency domain data, the method further includes:

[0019] Traverse each data block in the frequency domain data and remove the target high-frequency points in the data blocks.

[0020] In some embodiments, the Huffman coding uses a corresponding Huffman coding table based on the scanning scene corresponding to the original scanned image.

[0021] In some embodiments, the original scanned image is a black-and-white image or a color image.

[0022] Secondly, this embodiment provides an image data processing apparatus for three-dimensional scanning, the apparatus comprising:

[0023] A determination module is used to determine the target category to which each standard mapping table pre-stored by the computing unit belongs; the computing unit is pre-associated with a data compression unit used to generate image compressed files;

[0024] The compression module is used to compress the original scanned image based on a preset compression rule to obtain a corresponding compressed image file; the preset compression rule indicates that the compression process does not require the generation of a mapping table for the target category;

[0025] The decoding module is used to transmit the image compressed file to the computing unit and perform decoding processing on the image compressed file based on the standard mapping table corresponding to the image compressed file.

[0026] Thirdly, this embodiment provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the image data processing method in three-dimensional scanning described in the first aspect above.

[0027] Fourthly, this embodiment provides a storage medium storing a computer program that, when executed by a processor, implements the image data processing method in three-dimensional scanning described in the first aspect above.

[0028] Compared with related technologies, the image data processing method, apparatus, and computer equipment for 3D scanning provided in this embodiment, by determining the target category to which each standard mapping table pre-stored in the computing unit belongs; the computing unit being pre-associated with a data compression unit for generating image compressed files; compressing the original scanned image based on preset compression rules to obtain the corresponding image compressed file; the preset compression rules indicating that the compression process does not require generating a target category mapping table; and transmitting the image compressed file to the computing unit, and decoding the image compressed file based on the standard mapping table corresponding to the image compressed file, solves the problem of low 3D scanning efficiency caused by the significant influence of color image compressed data, which prevents efficient transmission of scanned data to the computing unit for calculation. This achieves efficient transmission of scanned data to the computing unit, improving 3D scanning efficiency.

[0029] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0031] Figure 1 This is a hardware structure block diagram of a terminal device for an image data processing method in three-dimensional scanning provided in an embodiment of this application;

[0032] Figure 2 This is a flowchart of an image data processing method in three-dimensional scanning provided in an embodiment of this application;

[0033] Figure 3This is a flowchart of a compressed file decoding method provided in an embodiment of this application;

[0034] Figure 4 This is a flowchart of a scanned image compression method provided in an embodiment of this application;

[0035] Figure 5 This is a flowchart of an image data processing method in three-dimensional scanning provided in another embodiment of this application;

[0036] Figure 6 This is a flowchart of an image data processing method in three-dimensional scanning provided in a preferred embodiment of this application;

[0037] Figure 7 This is a structural block diagram of an image data processing device for three-dimensional scanning provided in an embodiment of this application.

[0038] In the diagram: 102, processor; 104, memory; 106, transmission device; 108, input / output device; 10, determination module; 20, compression module; 30, decoding module. Detailed Implementation

[0039] To better understand the purpose, technical solution, and advantages of this application, the application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0040] Unless otherwise defined, the technical or scientific terms used in this application shall have the general meaning as understood by one of ordinary skill in the art to which this application pertains. Words such as “a,” “an,” “an,” “the,” “the,” and “these,” used in this application, do not indicate quantitative limitation and may be singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or modules (units) but may include steps or modules (units) not listed, or may include other steps or modules (units) inherent to such processes, methods, products, or devices. The terms “connected,” “linked,” and “coupled,” used in this application, are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. The term “multiple” used in this application refers to two or more. The "and / or" operator describes the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: A alone, A and B simultaneously, and B alone. Typically, the character " / " indicates that the objects before and after it are in an "or" relationship. The terms "first," "second," and "third," etc., used in this application are merely for distinguishing similar objects and do not represent a specific ordering of the objects.

[0041] The method embodiments provided in this example can be executed on a terminal, computer, or similar computing device. For example, it can run on a terminal. Figure 1 This is a hardware structure block diagram of the terminal for the image data processing method in the three-dimensional scanning of this embodiment. For example... Figure 1 As shown, a terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 and a memory 104 for storing data are also included. The processor 102 may be, but is not limited to, a microprocessor (MCU) or a programmable logic device (FPGA). The terminal may also include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that… Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the terminal described above. For example, the terminal may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown are illustrated.

[0042] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the image data processing method in 3D scanning in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0043] The transmission device 106 is used to receive or send data via a network. This network includes a wireless network provided by the terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 can be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0044] This embodiment provides an image data processing method for three-dimensional scanning. Figure 2 This is a flowchart of the image data processing method in the three-dimensional scanning of this embodiment, as follows: Figure 2As shown, the process includes the following steps:

[0045] Step S210: Determine the target category to which each standard mapping table pre-stored in the computing unit belongs; the computing unit is pre-associated with the data compression unit used to generate image compressed files;

[0046] Step S220: Based on preset compression rules, the original scanned image is compressed to obtain the corresponding image compressed file; the preset compression rules indicate that the compression process does not require the generation of a target category mapping table.

[0047] Step S230: The image compressed file is transmitted to the computing unit, and the image compressed file is decoded based on the standard mapping table corresponding to the image compressed file.

[0048] Specifically, the raw scanned image obtained by the image acquisition unit is typically in Bayer format. Based on preset compression rules, the raw scanned image is input into the data compression unit for compression processing. The calculation unit is associated with the data compression unit used to generate the compressed file. The target category of each standard mapping table in the calculation unit is predetermined, and corresponding preset compression rules are generated based on the target category of each standard mapping table. The preset compression rules indicate that the compression process does not require the generation of a mapping table for the target category.

[0049] During compression, the original scanned image is pre-segmented into image blocks of a preset size, typically 8x8. Each image block is then input into a Discrete Cosine Transform (DCT) module for processing, converting the image from the time domain to the frequency domain. This yields the frequency domain data for each image block, which is then quantized. The quantized frequency domain data is then subjected to run-length encoding and Huffman coding to produce the corresponding compressed image file. This compressed image file includes the compressed data corresponding to each image block in the original scanned image. It should be noted that the compression process of the original scanned image is based on preset compression rules, ensuring that the resulting compressed image file does not contain target category mapping tables, such as quantization tables or Huffman coding tables.

[0050] The computing unit is pre-associated with the data compression unit used to generate compressed files. This computing unit pre-stores a standard mapping table, which can be used for subsequent image decoding. The standard mapping table includes quantization tables, Huffman coding tables, etc., and can be set based on different scanning scenarios. For example, different scanning scenarios are distinguished based on different scanning objects and their scanning environments. A corresponding standard mapping table is set based on the image features acquired in each scanning scenario, ensuring that the standard mapping table is adapted to each scanning scenario and guaranteeing the image quality obtained after decoding. The image compressed file is transmitted to the computing unit, the scanning scenario associated with the image compressed file is determined, the standard mapping table corresponding to that scanning scenario is retrieved from the pre-set decoding algorithm library, and then the image compressed file is decoded based on the standard mapping table corresponding to the scanning scenario.

[0051] For example, if the computing unit pre-stores quantization tables, Huffman coding tables for the DC and AC components of luminance, it is indicated that the quantization tables, DC and AC components of luminance do not need to be generated during image compression. As a result, the compressed image file does not contain the quantization tables, DC and AC components of luminance. The compressed image file is then transmitted to the computing unit, the scanning scene associated with the compressed image file is determined, and the quantization tables, DC and AC components of luminance corresponding to the scanning scene are retrieved from the preset decoding algorithm library to decode the compressed image file.

[0052] It should be noted that in this embodiment, the original scanned images include black and white images and color images, both of which are compressed using the compression method described above. Specifically, color images do not require color space conversion or color chroma encoding, reducing algorithm complexity. Furthermore, black and white and color images can be processed uniformly, with compression completed within the same algorithm module.

[0053] In existing technologies, the original image data to be transmitted is pre-compressed before transmission. However, images acquired through 3D scanning typically include both black-and-white and color images. Black-and-white images are used for imaging, while color images are used for colorizing the imaged object. After processing by existing compression algorithms, the Huffman coding information of the color image occupies a significant amount of bandwidth during data transmission, forcing a reduction in the transmission frame rate. Consequently, when applying existing compression algorithms, the compression of the color image data has a significant impact, making it difficult to efficiently transmit the scanned data to the computing unit for calculation, resulting in low 3D scanning efficiency.

[0054] Compared to existing technologies, this application determines the target category of each standard mapping table pre-stored in the computing unit; the computing unit is pre-associated with a data compression unit used to generate image compressed files; the original scanned image is compressed based on preset compression rules to obtain the corresponding image compressed file; the preset compression rules indicate that the compression process does not require the generation of a mapping table for the target category; the image compressed file is transmitted to the computing unit, and the image compressed file is decoded based on the standard mapping table corresponding to the image compressed file. Based on this, the computing unit pre-stores a standard mapping table for decoding, thus eliminating the need to generate a mapping table of the same category as the standard mapping table during image compression. This ensures that the image compressed file to be transmitted does not contain a mapping table of the same category as the standard mapping table, reducing the amount of data to be transmitted, especially significantly reducing the amount of color image compressed data. This solves the problem of low 3D scanning efficiency caused by the significant impact of color image compressed data on efficient transmission of scanned data to the computing unit for calculation. This application achieves efficient transmission of scanned data to the computing unit, improving 3D scanning efficiency.

[0055] Among them, black and white images are key image data for 3D scanning imaging. Compared with color images, the quality of black and white images has a greater impact on the accuracy of 3D reconstruction. Because the Huffman compression information of color images in the compressed data processed by existing compression algorithms occupies a large amount of data bandwidth, existing data transmission methods actually consume a lot of time for color image data transmission. This application uses the same compression processing method for both black and white and color images, eliminating the need for color space conversion and considering image chromaticity encoding for color images. Furthermore, the image compressed file does not contain the mapping table pre-stored by the computing unit. While ensuring that the quality of black and white images is not affected, it significantly reduces the amount of data transmitted, improving the rationality of the overall data processing flow.

[0056] In some of these embodiments, such as Figure 3 As shown, step S230, which decodes the image compressed file based on the standard mapping table corresponding to the image compressed file, includes the following steps:

[0057] Step S231: Determine the scanning scene associated with the image compression file;

[0058] Step S232: Retrieve the standard mapping table corresponding to the scanning scene from the preset decoding algorithm library;

[0059] Step S233: Decode the image compressed file based on the standard mapping table corresponding to the scanning scene.

[0060] Specifically, when the computing unit receives the image compressed file, it determines the scanning scene associated with the image compressed file. It should be noted that when generating the compressed file, the scanning scene corresponding to the original scanned image can be determined simultaneously, so that the computing unit can determine the scanning scene associated with the image compressed file. Different scanning scenes are distinguished based on factors such as different scanning objects and different scanning environments in which the scanning objects are located. The scanning environment includes indoor and outdoor scanning, scanning under different lighting conditions, etc., such as scanning the target workpiece indoors.

[0061] Furthermore, the pre-stored decoding algorithm library contains standard mapping tables required for different scanning scenarios. After determining the current scanning scenario, the standard mapping table corresponding to that scanning scenario is retrieved from the decoding algorithm library, and the image compressed file is decoded based on the retrieved standard mapping table. For example, if the computing unit pre-stores quantization tables, Huffman coding tables for the DC and AC components of luminance, the corresponding quantization tables, DC and AC component coding tables for luminance are retrieved from the decoding algorithm library to decode the image compressed file.

[0062] In this embodiment, the scanning scene associated with the image compression file is determined, the standard mapping table corresponding to the scanning scene is retrieved from the preset decoding algorithm library, and the image compression file is decoded based on the standard mapping table corresponding to the scanning scene. Thus, based on the actual scanning scene, the appropriate standard mapping table is retrieved for decoding to ensure the quality of the decoded image.

[0063] In some of these embodiments, the standard mapping table includes a quantization table and / or a Huffman coding table.

[0064] Specifically, in the computing unit associated with the data compression unit, standard quantization tables adapted to different scanning scenarios are pre-stored. Based on the mapping tables required for image compression and decoding, the standard mapping tables in this embodiment include quantization tables, Huffman coding tables, etc. The quantization table provides a corresponding quantization factor for each DCT coefficient, used to quantize the DCT coefficients during image compression to reduce the precision of high-frequency information and achieve further data compression. The Huffman coding table is a set of coding rules that allocate binary codes of different lengths based on different frequencies of occurrence, aiming to reduce the storage requirements of the quantized data.

[0065] For example, the computing unit pre-stores standard quantization tables and Huffman coding tables for the DC and AC components of luminance. Pre-defined compression rules instruct that corresponding quantization tables and Huffman coding tables for the DC and AC components of luminance are not needed during image compression, thus compressing the image into a compressed image file that does not contain quantization tables or Huffman coding tables. When the computing unit receives the compressed image file, it determines the scanning scene associated with the compressed image file and retrieves the corresponding quantization table, DC component, and AC component Huffman coding tables from a pre-defined decoding algorithm library to decode the compressed image file.

[0066] In this embodiment, multiple standard mapping tables for subsequent decoding are pre-stored in the computing unit, so that the image compression file does not need to contain mapping tables of the same category as the standard mapping tables, thereby reducing the amount of data to be transmitted and increasing the effective bandwidth of data transmission.

[0067] In some of these embodiments, such as Figure 4 As shown, step S220, which involves compressing the original scanned image to obtain a corresponding compressed image file, includes the following steps:

[0068] Step S221: Convert the original scanned image into the corresponding frequency domain data;

[0069] Step S222: Quantize the frequency domain data;

[0070] Step S223: Perform run-length encoding and Huffman encoding on the quantized frequency domain data to obtain the corresponding image compressed file.

[0071] Specifically, the original scanned image is pre-segmented to obtain image blocks of a preset size, typically 8x8. Each image block is then input into a discrete cosine transform module for processing, converting the image from the time domain to the frequency domain to obtain the frequency domain data corresponding to each image block. The frequency domain data for each image block is then quantized to further compress the data by reducing the amount of high-frequency information.

[0072] After the discrete cosine transform and quantization processes described above, the high-frequency information of the image often becomes sparse, meaning many DCT coefficients will be quantized to zero. Run-length encoding is used to encode the quantized data, unifying the zeros in the data. For example, a partial DCT coefficient sequence after quantization might be [8,0,0,0,5]. Run-length encoding converts this to (8,1), (0,3), and (5,1), thus compressing multiple zero values ​​into a single code and reducing the number of codes. Next, entropy encoding is used to process the data. This involves setting the code length based on the probability of different symbols appearing in the data to be encoded, constructing a corresponding Huffman coding tree, and mapping the run-length encoding result to complete the encoding and obtain the corresponding compressed image file. This compressed image file includes compressed data corresponding to each image block in the original scanned image, the quantization table from the quantization process, and the Huffman coding table from the encoding stage.

[0073] In this embodiment, the original scanned image is converted into corresponding frequency domain data, the frequency domain data is quantized, and the quantized frequency domain data is then subjected to run-length encoding and Huffman encoding to obtain the corresponding image compressed file, thereby completing the compression processing of the original scanned image.

[0074] In some embodiments, after quantizing the frequency domain data, the following steps are also included:

[0075] Traverse each data block in the frequency domain data and remove the target high-frequency points in the data blocks.

[0076] It should be noted that after discrete cosine transform and quantization, some image blocks often have no data in the middle but data at the end. For example, for a certain image block after discrete cosine transform and quantization, the quantization result is as follows:

[0077] [10,5,0,0,0,0,0,0

[0078] 6,2,0,0,0,0,0,0

[0079] 0,0,0,0,0,0,0,0

[0080] 0,0,0,0,0,0,0,4]

[0081] In this dataset, the first data point at the front is designated as 2, and the second data point at the back is designated as 4, with 21 zero data points between them. In this scenario, the high-frequency points at the back have little impact on the actual image quality recovery; that is, removing these high-frequency points will not affect the image's visual quality. Therefore, the second data point can be defined as 0. Based on this, after quantization, each data block in the frequency domain data can be traversed, and the target high-frequency points in the data blocks can be removed, further reducing the data volume without affecting the image's visual quality.

[0082] In this embodiment, by traversing each data block in the frequency domain data and removing the target high-frequency points in the data blocks, it is helpful to improve the effective bandwidth of subsequent data transmission.

[0083] In some of these embodiments, Huffman coding employs a corresponding Huffman coding table based on the scanning scene corresponding to the original scanned image.

[0084] Specifically, after performing Discrete Cosine Transform (DCT) and quantization on each image patch, the high-frequency information of the image often becomes sparse, meaning that many DCT coefficients will be quantized to zero. Based on this, the quantized data is pre-encoded using run-length encoding to uniformly process the zeros in the data. For example, if a part of the quantized DCT coefficient sequence is [8,0,0,0,5], run-length encoding can be used to convert it to (8,1), (0,3), (5,1), thereby compressing multiple zero values ​​in the data into a single code and reducing the number of codes.

[0085] Furthermore, entropy coding is used to process the run-length encoded data to obtain the corresponding image compressed file. Specifically, the encoding length is set according to the probability of different symbols appearing in the data to be encoded, a corresponding Huffman coding tree is constructed, and the results of run-length encoding are mapped to complete the encoding, resulting in the image compressed file. This image compressed file includes compressed data corresponding to each image block in the original scanned image, a quantization table from the quantization process, and a Huffman coding table from the encoding stage. In this embodiment, arithmetic coding or other algorithms can also be used to encode the run-length encoded data.

[0086] It should be noted that, based on the different scanning scenarios corresponding to different original scanned images, the Huffman coding process can employ corresponding Huffman coding tables for encoding. Different scanning scenarios can be defined according to factors such as the scanning object and the scanning environment. For example, for a scanning scenario where the target workpiece is scanned indoors, a corresponding Huffman coding table can be set.

[0087] In this embodiment, Huffman coding uses a corresponding Huffman coding table based on the scanning scene corresponding to the original scanned image. This allows for adaptive optimization of the image compression method based on different scanning scenes, improving compression efficiency and helping to reduce image distortion and improve image quality.

[0088] In some of these embodiments, the original scanned image is a black and white image or a color image.

[0089] Specifically, the original scanned images include black and white images and color images. Black and white images help extract the shape and structural features of the scanned object and are usually used for imaging, while color images provide richer visual information and are used to color the imaged object, which helps in the 3D reconstruction of the scanned object's true appearance.

[0090] When processing images using existing compression algorithms, compared to the compression process for black and white images, color images require a color space conversion beforehand. This involves interpolating the color image to an RGB image, then converting it to the YUV color space, and finally performing encoding. This requires additional consideration of image chroma during the color image encoding process, increasing the number of Huffman coding tables in the encoding stage and resulting in the Huffman compression information for color images consuming a larger amount of data bandwidth. In this embodiment, however, black and white images and color images use the same compression processing method. Color images do not require color space conversion or consideration of image chroma encoding, reducing algorithm complexity. Furthermore, black and white and color images can be processed uniformly, with compression completed within the same algorithm module. The specific compression processing method has been described in the above embodiments and will not be repeated here.

[0091] It should be further explained that in 3D scanning, black and white images are key image data for scanning imaging. Compared with color images, the quality of black and white images has a greater impact on the accuracy of 3D reconstruction. In compressed data processed by existing compression algorithms, the Huffman compression information of color images occupies a large amount of data bandwidth. It can be seen that color images are the main factor causing the inefficient transmission of scanned data to the computing unit. Existing data transmission methods actually consume a lot of time for color image data transmission, resulting in an unreasonable overall data processing flow. In this embodiment, the target category of each standard mapping table in the computing unit is determined in advance, and corresponding preset compression rules are generated based on the target category of each standard mapping table. The preset compression rules limit the compression process from generating the target category mapping table. When performing image compression processing, the preset compression rules are used to indicate that the compression process does not need to generate the target category mapping table, so that the compressed image file does not contain the mapping table belonging to the target category, effectively reducing the data volume of the compressed image file. Thus, while ensuring that the quality of black and white images is not affected, the amount of data transmitted is significantly reduced.

[0092] This embodiment demonstrates that the same compression process can be used for both black-and-white and color images of the original scanned image, reducing algorithm complexity. Furthermore, it ensures that the quality of the black-and-white image is not affected, while avoiding the impact of color image compression on the efficient transmission of scanned data, thus improving the overall rationality of the data processing flow.

[0093] This embodiment also provides an image data processing method for three-dimensional scanning. Figure 5 This is a flowchart of another image data processing method in three-dimensional scanning according to this embodiment, such as... Figure 5 As shown, the process includes the following steps:

[0094] Step S510: Obtain the first compressed file corresponding to the original scanned image;

[0095] Step S520: Determine the target category to which each standard mapping table in the computing unit belongs; wherein, the computing unit is pre-associated with the data compression unit used to generate compressed files; each standard mapping table is pre-stored in the computing unit;

[0096] Step S530: Remove the mapping table belonging to the target category from the first compressed file to obtain the second compressed file;

[0097] Step S540: The second compressed file is transmitted to the computing unit, and the second compressed file is decoded based on the standard mapping table corresponding to the second compressed file.

[0098] Specifically, the original scanned image obtained by the image acquisition unit is acquired. This original scanned image includes both black-and-white and color images. During image compression, the original scanned image is pre-segmented to obtain multiple 8*8 image blocks. Each image block undergoes discrete cosine transformation to convert the image from the time domain to the frequency domain, obtaining the frequency domain data corresponding to each image block. The frequency domain data corresponding to each image block is then quantized. The quantized frequency domain data is then subjected to run-length encoding and Huffman encoding to obtain the corresponding first compressed file. This first compressed file includes the compressed data corresponding to each image block in the original scanned image, the quantization table from the quantization process, and the Huffman encoding table from the encoding stage.

[0099] It should be noted that the computing unit is pre-associated with the data compression unit used to generate compressed files, and the computing unit pre-stores a standard mapping table, which can be used for subsequent image decoding. This standard mapping table includes quantization tables, Huffman coding tables, etc. The standard mapping table can be set based on different scanning scenarios. For example, different scanning scenarios can be distinguished based on different scanning objects and the different scanning environments in which the scanning objects are located. Based on the image features acquired in each scanning scenario, a corresponding standard mapping table is set to ensure that the standard mapping table is adapted to each scanning scenario, thus ensuring the quality of the subsequently decoded images.

[0100] Furthermore, the target category of each standard mapping table in the computing unit is determined, and mapping tables belonging to the target category in the first compressed file are filtered out. These mapping tables are then removed from the first compressed file to obtain the second compressed file. This process removes mapping tables from the first compressed file that do not need to be transmitted, significantly reducing data transmission volume. The second compressed file is transmitted to the computing unit, and the scanning scene associated with it is determined. The standard mapping table corresponding to this scanning scene is retrieved from a pre-set decoding algorithm library, and then the second compressed file is decoded based on this standard mapping table. For example, if the computing unit pre-stores quantization tables, Huffman coding tables for the DC and AC components of luminance, these tables are removed from the first compressed file to obtain the second compressed file to be transmitted. The second compressed file is then transmitted to the computing unit, and the scanning scene associated with it is determined. The quantization table, Huffman coding tables for the DC and AC components of luminance corresponding to this scanning scene are retrieved from the pre-set decoding algorithm library, and the second compressed file is decoded.

[0101] In this embodiment, a first compressed file corresponding to the original scanned image is obtained, the target category to which each standard mapping table in the computing unit belongs is determined, the mapping table belonging to the target category in the first compressed file is removed, a second compressed file is obtained, and the second compressed file is transmitted to the computing unit. Based on the standard mapping table corresponding to the second compressed file, the second compressed file is decoded. In this way, with the standard mapping table pre-stored in the computing unit, the mapping table of the same category as the standard mapping table in the compressed file to be transmitted can be removed, thereby reducing the amount of data to be transmitted, especially significantly reducing the compressed data of color images, realizing efficient transmission of scanned data to the computing unit and improving the efficiency of 3D scanning.

[0102] The present embodiment will now be described and illustrated through preferred embodiments.

[0103] Figure 6 This is a flowchart of the image data processing method in three-dimensional scanning according to a preferred embodiment, as follows: Figure 6 As shown, the image data processing method in this 3D scan includes the following steps:

[0104] Step S610: Determine the target category to which each standard mapping table pre-stored in the computing unit belongs; the computing unit is pre-associated with the data compression unit used to generate image compressed files;

[0105] Step S620: Based on preset compression rules, the original scanned image is converted into corresponding frequency domain data, the frequency domain data is quantized, and the quantized frequency domain data is run-length encoded and Huffman encoded to obtain the corresponding image compressed file; the preset compression rules indicate that the compression process does not require the generation of a target category mapping table;

[0106] Step S630: The image compression file is transferred to the computing unit;

[0107] Step S640: Determine the scanning scene associated with the image compression file and retrieve the standard mapping table corresponding to the scanning scene from the preset decoding algorithm library;

[0108] Step S650: Decode the image compressed file based on the standard mapping table corresponding to the scanning scene.

[0109] In this embodiment, the target category of each standard mapping table pre-stored by the computing unit is predetermined, and the computing unit is pre-associated with the data compression unit used to generate image compressed files. Based on preset compression rules, the original scanned image is converted into corresponding frequency domain data, the frequency domain data is quantized, and the quantized frequency domain data is subjected to run-length encoding and Huffman encoding to obtain the corresponding image compressed file. The preset compression rules indicate that the compression process does not need to generate a mapping table for the target category, ensuring that the image compressed file does not contain a mapping table of the same category as the standard mapping table, thereby reducing the amount of data to be transmitted and increasing the effective bandwidth of data transmission.

[0110] Furthermore, the image compressed file is transmitted to the computing unit, the scanning scene associated with the image compressed file is determined, the standard mapping table corresponding to the scanning scene is retrieved from the preset decoding algorithm library, and the image compressed file is decoded based on the standard mapping table corresponding to the scanning scene. This solves the problem that the scanning data cannot be efficiently transmitted to the computing unit for calculation due to the large influence of color image compressed data, resulting in low 3D scanning efficiency. It realizes efficient transmission of scanning data to the computing unit and improves 3D scanning efficiency.

[0111] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0112] This embodiment also provides an image data processing apparatus for three-dimensional scanning, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. The terms "module," "unit," "subunit," etc., used below refer to combinations of software and / or hardware that perform a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0113] Figure 7 This is a structural block diagram of the image data processing device in the three-dimensional scanning of this embodiment, as shown below. Figure 7 As shown, the device includes:

[0114] The determination module 10 is used to determine the target category to which each standard mapping table pre-stored in the computing unit belongs; the computing unit is pre-associated with the data compression unit used to generate image compressed files;

[0115] Compression module 20 is used to compress the original scanned image based on preset compression rules to obtain the corresponding image compressed file; the preset compression rules indicate that the compression process does not need to generate a target category mapping table;

[0116] The decoding module 30 is used to transmit the image compressed file to the computing unit and perform decoding processing on the image compressed file based on the standard mapping table corresponding to the image compressed file.

[0117] The apparatus provided in this embodiment determines the target category to which each standard mapping table pre-stored in the computing unit belongs; the computing unit is pre-associated with the data compression unit used to generate image compressed files; based on preset compression rules, the original scanned image is compressed to obtain the corresponding image compressed file; the preset compression rules indicate that the compression process does not require the generation of a target category mapping table; the image compressed file is transmitted to the computing unit, and based on the standard mapping table corresponding to the image compressed file, the image compressed file is decoded. This solves the problem that the scanning data cannot be efficiently transmitted to the computing unit for calculation due to the significant influence of color image compressed data, resulting in low 3D scanning efficiency. It achieves efficient transmission of scanning data to the computing unit, thereby improving 3D scanning efficiency.

[0118] In some embodiments, the decoding module 30 is further configured to determine the scanning scene associated with the image compressed file; retrieve the standard mapping table corresponding to the scanning scene from a preset decoding algorithm library; and perform decoding processing on the image compressed file based on the standard mapping table corresponding to the scanning scene.

[0119] In some embodiments, the compression module 20 is further configured to convert the original scanned image into corresponding frequency domain data; quantize the frequency domain data; and perform run-length encoding and Huffman encoding on the quantized frequency domain data to obtain the corresponding image compressed file.

[0120] In some of these embodiments, Figure 7 Based on this, the device also includes a filtering module, which is used to traverse each data block in the frequency domain data, determine the target high-frequency point in each data point based on the number of consecutive zero data between different data points in the data block and the location of the data point; and remove the target high-frequency point in the data block.

[0121] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0122] This embodiment also provides a computer device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0123] Optionally, the computer device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0124] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0125] S1, determine the target category to which each standard mapping table pre-stored in the computing unit belongs; the computing unit is pre-associated with the data compression unit used to generate image compressed files;

[0126] S2, based on preset compression rules, compresses the original scanned image to obtain the corresponding compressed image file; the preset compression rules indicate that the compression process does not require the generation of a target category mapping table;

[0127] S3 transmits the image compressed file to the computing unit and decodes the image compressed file based on the standard mapping table corresponding to the image compressed file.

[0128] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated in this embodiment.

[0129] Furthermore, in conjunction with the image data processing method for three-dimensional scanning provided in the above embodiments, this embodiment can also provide a storage medium for implementation. The storage medium stores a computer program; when executed by a processor, the computer program implements any of the image data processing methods for three-dimensional scanning described in the above embodiments.

[0130] It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. All other embodiments derived by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0131] Obviously, the accompanying drawings are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar situations based on these drawings without any creative effort. Furthermore, it is understood that although the work done in this development process may be complex and lengthy, for those skilled in the art, certain design, manufacturing, or production modifications made based on the technical content disclosed in this application are merely conventional technical means and should not be considered as insufficient disclosure of this application.

[0132] The term "embodiment" in this application refers to a specific feature, structure, or characteristic described in connection with an embodiment that may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily imply the same embodiment, nor does it imply that it is mutually exclusive with or independent of other embodiments. It will be clearly or implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0133] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of patent protection. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims

1. An image data processing method in three-dimensional scanning, characterized in that, The method includes: The target category to which each standard mapping table pre-stored in the computing unit belongs is determined; the computing unit is pre-associated with a data compression unit used to generate image compressed files; Based on preset compression rules, the original scanned image is compressed to obtain the corresponding compressed image file; the preset compression rules indicate that the compression process does not require the generation of a mapping table for the target category; The image compressed file is transmitted to the computing unit, and the image compressed file is decoded based on the standard mapping table corresponding to the image compressed file.

2. The image data processing method in three-dimensional scanning according to claim 1, characterized in that, The decoding process of the image compressed file based on the standard mapping table corresponding to the image compressed file includes: Determine the scanning scene associated with the image compression file; Retrieve the standard mapping table corresponding to the scanning scene from the preset decoding algorithm library; The image compressed file is decoded based on the standard mapping table corresponding to the scanning scene.

3. The image data processing method in three-dimensional scanning according to claim 1, characterized in that, The standard mapping table includes a quantization table and / or a Huffman coding table.

4. The image data processing method in three-dimensional scanning according to claim 1, characterized in that, The process of compressing the original scanned image to obtain a corresponding compressed image file includes: The original scanned image is converted into corresponding frequency domain data; The frequency domain data is quantized. The quantized frequency domain data is then subjected to run-length encoding and Huffman encoding to obtain the corresponding image compressed file.

5. The image data processing method in three-dimensional scanning according to claim 4, characterized in that, After quantizing the frequency domain data, the method further includes: Traverse each data block in the frequency domain data and remove the target high-frequency points in the data blocks.

6. The image data processing method in three-dimensional scanning according to claim 4, characterized in that, The Huffman coding uses a corresponding Huffman coding table based on the scanning scene corresponding to the original scanned image.

7. The image data processing method in three-dimensional scanning according to any one of claims 1 to 6, characterized in that, The original scanned image is either a black and white image or a color image.

8. An image data processing device for three-dimensional scanning, characterized in that, The device includes: A determination module is used to determine the target category to which each standard mapping table pre-stored by the computing unit belongs; the computing unit is pre-associated with a data compression unit used to generate image compressed files; The compression module is used to compress the original scanned image based on a preset compression rule to obtain a corresponding compressed image file; the preset compression rule indicates that the compression process does not require the generation of a mapping table for the target category; The decoding module is used to transmit the image compressed file to the computing unit and perform decoding processing on the image compressed file based on the standard mapping table corresponding to the image compressed file.

9. A computer device, comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the steps of the image data processing method in three-dimensional scanning according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the image data processing method in three-dimensional scanning as described in any one of claims 1 to 7.

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