Multi-resolution panoramic video image lossless transmission method and device

Abstract

The invention provides a multi-resolution panoramic video image lossless transmission method and device. The technical problem that performance conflicts exist between existing video image transmission code streams and image quality is solved. The method comprises the following steps: forming image lossless coding context signals of a panoramic video image under multiple resolutions by using coding position correlation of wavelet coefficients; and performing wavelet function basis decomposition on the panoramic video image transmission signal after translation processing to form a high-frequency sub-band and a low-frequency sub-band for compression coding. A panoramic video image is decomposed into components under different resolutions, and sparse representation and lossless coding are performed on each component by using a wavelet function base, so that efficient transmission of a multi-resolution image is realized. The algorithm has the advantages of high transmission efficiency and high image quality, and a new thought is provided for development of the panoramic video image transmission field.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and particularly relates to a method and device for lossless transmission of panoramic video images at multiple resolutions. Background Art

[0002] With the development of emerging technologies such as virtual reality (VR) and augmented reality (AR), the demand for panoramic video image transmission is increasing day by day. Due to its high resolution, large amount of data, and high requirements for transmission speed, panoramic video images are challenging in real-time transmission and storage. Traditional lossless coding algorithms often struggle to meet the requirements of real-time transmission while ensuring image quality. Therefore, developing an efficient lossless coding algorithm for panoramic video images is of great significance for meeting the future demand for high-quality image transmission in virtual reality applications. In the prior art, for the coding algorithm for 6G panoramic video slice division, the input panoramic video is divided into multiple segments according to the scene content, each segment is encoded, and a suitable coding algorithm is used to compress the video segments to reduce the data volume. During the coding process, the algorithm is optimized according to the content and quality of the video segments to maintain the original quality and visual effect of the image. The coding algorithm based on entropy balance encodes each macroblock and makes adaptive adjustments according to factors such as network bandwidth and device performance to achieve more efficient video transmission and playback. The lossless coding algorithm based on Walsh-Hadmard butterfly transform preprocesses the input image and divides it into multiple sub-blocks. The image is transformed from the spatial domain to the transform domain, where the energy concentration of the image is higher, so lossless coding can be better performed. However, when dealing with high-resolution panoramic images, the above three algorithms require a large amount of context information, resulting in high computational complexity and poor real-time performance.

[0003] In the prior art, as a signal processing technology, wavelet transform can decompose an image into sub-band coefficients at different scales and directions. These coefficients reflect the information of the image at different frequencies and positions. By performing quantization coding on the sub-band coefficients, image compression can be achieved. The quantization process usually involves retaining larger coefficients and discarding smaller coefficients, thereby reducing the data volume and achieving higher compression efficiency and image quality. But it is mostly applied to the compression processing of single-resolution static images, such as the coding system of JPEG 2000. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a method and device for lossless transmission of panoramic video images at multiple resolutions, which solve the technical problem of the performance conflict between the existing video image transmission code stream and the image quality.

[0005] The method for lossless transmission of panoramic video images at multiple resolutions according to the embodiments of the present invention includes:

[0006] The coding position correlation of wavelet coefficients is used to form the image lossless coding context signal of panoramic video images at multiple resolutions.

[0007] The high and low frequency sub-bands for compression coding are formed by performing wavelet function decomposition on the panoramic video image transmission signal after translation processing.

[0008] In one embodiment of the present invention, the method of forming a lossless coding context signal of a panoramic video image at multiple resolutions by utilizing coding position correlation of wavelet coefficients includes:

[0009] Forming panoramic video image transmission signals at multiple resolutions;

[0010] Determining the positional state between the wavelet coefficients to be encoded of the panoramic video image transmission signal;

[0011] A context signal model for lossless image coding at multiple resolutions is formed according to the positional states of the wavelet coefficients to be coded.

[0012] In one embodiment of the present invention, the position status between the wavelet coefficients to be coded includes the brother nodes or

[0013] The brother nodes of the wavelet coefficient to be coded in the horizontal, vertical and diagonal directions on the same coding layer and the parent node of the previous coding layer.

[0014] In one embodiment of the present invention, when the multi-resolution image lossless coding context signal has no parent node:

[0015] When the wavelet coefficients to be coded A(x,y) are in the horizontal or vertical layer to be coded, the context signal model for lossless coding of images at multiple resolutions is expressed as:

[0016]

[0017] in, represents the context quantization operator; A(x,y) represents the wavelet coefficient to be coded with the horizontal coordinate x and the vertical coordinate y; h x 、k y Represents the encoding information in the horizontal or vertical direction respectively;

[0018] When the wavelet coefficients to be coded A(x,y) are in the diagonal layer to be coded, the context signal model for lossless coding of the image at multiple resolutions is expressed as:

[0019]

[0020] In one embodiment of the present invention, when the multi-resolution image lossless coding context signal has a parent node:

[0021] When the coefficient A(x, y) to be encoded is in the layer to be encoded in the horizontal or vertical direction, the context signal model for lossless image coding at multiple resolutions is expressed as:

[0022]

[0023] Where, represents the context quantization operator; A(x, y) represents the wavelet coefficient to be encoded with abscissa x and ordinate y; h x , k y respectively represent the coding information in the horizontal or vertical direction;

[0024] When the coefficient A(x, y) to be encoded is in the layer to be encoded in the diagonal direction, the context signal model for lossless image coding at multiple resolutions is expressed as:

[0025]

[0026] In an embodiment of the present invention, the wavelet function basis decomposition of the panoramic video image transmission signal after translation processing to form high-frequency and low-frequency subbands for compression coding includes:

[0027] Performing odd signal unit translation on the panoramic video image transmission signal to form a related transmission signal;

[0028] Performing wavelet analysis on the panoramic video image transmission signal and the related transmission signal to form high-frequency and low-frequency subbands;

[0029] Using a one-dimensional wavelet lifting mode for signal processing during the coding process.

[0030] In an embodiment of the present invention, the high-frequency and low-frequency subbands are:

[0031]

[0032] Where, γ represents the downsampling operator; ι represents the translation operator; represents the lossless coding context; η a , η b respectively represent the wavelet function bases of the high-frequency and low-frequency subbands.

[0033] In an embodiment of the present invention, the one-dimensional wavelet lifting mode for signal processing mainly includes:

[0034] Splitting the panoramic video image transmission signal a i into two subsets through the signal index u, namely the high-frequency subband index subset and the low-frequency subband index subset, which are respectively expressed as:

[0035]

[0036] Predict the low-frequency subband index subset using the high-frequency subband index subset, and obtain the prediction error Δe(u):

[0037]

[0038] Among them, represents the predicted low-frequency subband index subset;

[0039] Combined with the prediction error, update the high-frequency subband index subset, and the updated high-frequency subband index subset can be expressed as:

[0040]

[0041] Among them, θ represents the lifting factor, which is used to control the update amplitude.

[0042] The lossless transmission device for panoramic video images at multiple resolutions according to an embodiment of the present invention includes:

[0043] A memory for storing program codes during the processing of the lossless transmission method for panoramic video images at multiple resolutions as described in any one of claims 1 to 8;

[0044] A processor for executing the program codes.

[0045] The lossless transmission device for panoramic video images at multiple resolutions according to an embodiment of the present invention includes:

[0046] A coefficient correlation generation module for forming a lossless coding context signal of a panoramic video image at multiple resolutions by using the coding position correlation of wavelet coefficients;

[0047] A subband decomposition generation module for performing wavelet function basis decomposition on the panoramic video image transmission signal after translation processing to form high and low frequency subbands for compression coding.

[0048] The lossless transmission method and device for panoramic video images at multiple resolutions according to an embodiment of the present invention decompose the panoramic video image into components at different resolutions, and use wavelet function basis to perform sparse representation and lossless coding on each component, thereby realizing the efficient transmission of multi-resolution images. This algorithm has the advantages of high transmission efficiency and high image quality, providing a new idea for the development of the panoramic video image transmission field. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 The flowchart of the lossless transmission method for panoramic video images at multiple resolutions according to an embodiment of the present invention is shown.

[0050] Figure 2The figure shows a schematic diagram of the relevant positions of the wavelet coefficients to be encoded in the lossless coding context model of panoramic video images at multiple resolutions in an embodiment of the present invention.

[0051] Figure 3 The figure shows a schematic diagram of the local details of the original panoramic video image during the application process of the method for lossless transmission of panoramic video images at multiple resolutions in an embodiment of the present invention.

[0052] Figure 4 The figure shows a comparison schematic diagram with the coded pattern restored after being processed by each compression coding method during the application process of the method for lossless transmission of panoramic video images at multiple resolutions in an embodiment of the present invention.

[0053] Figure 5 The figure shows a schematic diagram of the architecture of the device for lossless transmission of panoramic video images at multiple resolutions in an embodiment of the present invention. Detailed implementation manners

[0054] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described below with reference to the accompanying drawings and specific implementation manners. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0055] The method for lossless transmission of panoramic video images at multiple resolutions in an embodiment of the present invention is as Figure 1 shown. In Figure 1 , this embodiment includes:

[0056] Step 100: Form a lossless coding context signal of the panoramic video image at multiple resolutions by using the coding position correlation of wavelet coefficients.

[0057] The technical idea of multi-resolution analysis is mainly that the wavelet transform coefficients can be dynamically reflected with the change of time in the time domain and frequency domain. When the frequency domain parameter is small, the observable field of view is narrow, with high resolution in the time domain and low resolution in the frequency domain, which can be used to observe signal details. When the frequency domain parameter is large, the observable field of view is wide, with low resolution in the time domain and high resolution in the frequency domain, which can be used to observe the overall picture of the signal.

[0058] Based on the transmission signal of the panoramic video image at multiple resolutions, the correlation relationship is formed by using wavelet coefficients to estimate the probability of each variable state. The importance degree of wavelet coefficients is closely related not only to the importance degree of adjacent coefficients, but also to the importance degree of the same-level child nodes and the upper-level child nodes at the same level.

[0059] By utilizing the image information at different resolutions, the image is compressed more effectively, thereby reducing the data size and improving the compression efficiency. Further, by leveraging the wavelet coefficient correlation in constructing the lossless coding context signal of the image, the lossless coding is not easily tampered with, enhancing the security of image transmission.

[0060] Step 200: Perform wavelet function basis decomposition on the panoramic video image transmission signal after translation processing to form high-frequency and low-frequency subbands for compression coding.

[0061] The wavelet function basis can decompose the signal into components of different frequencies. The wavelet function basis has the property of sparse coding, which can decompose the signal into a small number of wavelet coefficients, and most of the wavelet coefficients are almost zero. Since the coding context signal contains noise and redundant information, this sparse representation can separate the mutation part and the noise part in the signal, thereby reducing the fitting error of the mutation signal.

[0062] After forming the correlation signal by performing translation processing on the lossless coding context signal of the same image and then performing different wavelet function basis decompositions to form high-frequency and low-frequency subbands and the corresponding subband coefficients, the change of the subband coefficients is used to reflect the coefficient fluctuation of the panoramic video image at the image edge under multiple resolutions. Furthermore, layer-by-layer lossless coding compression of the high-frequency and low-frequency subbands is formed.

[0063] The lossless transmission method of panoramic video images under multiple resolutions in the embodiments of the present invention realizes the efficient transmission of multi-resolution images by decomposing the panoramic video image into components under different resolutions and using the wavelet function basis to perform sparse representation and lossless coding on each component. This algorithm has the advantages of high transmission efficiency and high image quality, providing a new technical idea for the development of the panoramic video image transmission field.

[0064] As Figure 1 shown, in an embodiment of the present invention, step 100 includes:

[0065] Step 110: Form a panoramic video image transmission signal under multiple resolutions.

[0066] Let θ i be the approximation of the spatial function at resolution 2 i Then the resolution at i + 1 can be expressed as:

[0067]

[0068] In formula (1), represents the orthogonal complement of the i-th θ i at resolution 9 + 1.

[0069] Let g i be the resolution 2i hour The orthogonal projection operator on , then the resolution is 2 i The panoramic video image transmission signal can be expressed as:

[0070]

[0071] In formula (2), Indicates the initial signal.

[0072] Step 120: Determine the position status of the wavelet coefficients to be encoded in the panoramic video image transmission signal.

[0073] Transmitting a panoramic video signal based on multiple resolutions i Based on the correlation between wavelet coefficients, the state probability of each variable is estimated. The importance of wavelet coefficients is closely related to the importance of adjacent coefficients, as well as the importance of the same-level child nodes and the upper-level child nodes on the same level.

[0074] The relative positions of the wavelet coefficients to be coded are as follows Figure 2 As shown. Figure 2 Middle C a 、C b and C d They represent the horizontal, vertical and diagonal brother nodes of the wavelet coefficient A to be coded in the same coding layer respectively; O represents the parent node of the previous coding layer of the wavelet coefficient A to be coded.

[0075] The importance of the eight neighboring pixels of the wavelet coefficient to be coded is combined with the importance of the sibling nodes and parent nodes to form an information expression that is independent of event relationships. Adaptive selection of sibling nodes is achieved by adaptively selecting the sub-band to which the wavelet coefficient to be coded belongs. Based on the different coding layer positions of the wavelet coefficient to be coded, the coding context construction is divided into two cases: Case 1, where the wavelet coefficient to be coded A(x,y) has no parent node, and Case 2, where the wavelet coefficient to be coded A(x,y) has a parent node.

[0076] Step 130: forming a context signal model for lossless image coding at multiple resolutions according to the positional states of the wavelet coefficients to be coded.

[0077] In case 1 (wavelet coefficient A(x,y) to be encoded has no parent node):

[0078] When the wavelet coefficients to be coded A(x,y) are in the horizontal or vertical layer to be coded, the context signal model for lossless coding of the image at multiple resolutions is expressed as:

[0079]

[0080] In formula (3), represents the context quantization operator; A(x, y) represents the wavelet coefficient to be encoded with the abscissa x and ordinate y; h x , k y respectively represent the encoding information in the horizontal or vertical direction.

[0081] When the wavelet coefficient A(x, y) to be encoded is in the layer to be encoded in the diagonal direction, the lossless coding context signal model of the image at multiple resolutions is expressed as:

[0082]

[0083] In Case 2 (the wavelet coefficient A(x, y) to be encoded has a parent node):

[0084] When the coefficient A(x, y) to be encoded is in the layer to be encoded in the horizontal or vertical direction, the lossless coding context signal model of the image at multiple resolutions is expressed as:

[0085]

[0086] When the coefficient A(x, y) to be encoded is in the layer to be encoded in the diagonal direction, the lossless coding context signal model of the image at multiple resolutions is expressed as:

[0087]

[0088] The lossless transmission method of panoramic video images at multiple resolutions in the embodiments of the present invention forms a lossless coding context signal model of the image at multiple resolutions, utilizes the image information at different resolutions, compresses the image more effectively, thereby reducing the size of the data and improving the compression efficiency. By constructing a lossless coding context signal model of the image, the lossless coding is not easily tampered with, so the security of image transmission can be enhanced.

[0089] As Figure 1 shown, in an embodiment of the present invention, step 200 includes:

[0090] Step 210: Perform odd-signal unit translation on the panoramic video image transmission signal to form a related transmission signal.

[0091] The panoramic video image transmission signal a i is translated by an odd number of units to form a related transmission signal. The positive and negative directions of the frequency components of the two signals are different, and two different-frequency wavelet analyses of the same signal can be formed.

[0092] Step 220: Perform wavelet analysis on the panoramic video image transmission signal and the related transmission signal to form high-frequency subbands and low-frequency subbands.

[0093] The related transmission signal is formed from the panoramic video image transmission signal ai It is formed by translating an odd number of units. The calculation formulas for the high-frequency and low-frequency subbands are as follows:

[0094]

[0095] In formula (7), γ represents the downsampling operator; ι represents the translation operator; represents the lossless coding context; η a and η b respectively represent the wavelet function bases of the high-frequency and low-frequency subbands.

[0096] Since the coding context contains noise and redundant information, the wavelet function basis can decompose the signal into components of different frequencies. The wavelet function basis has the property of sparse coding, which can decompose the signal into a small number of wavelet coefficients, but most of the wavelet coefficients are almost 0. This sparse representation can separate the mutation part and the noise part in the signal, thereby reducing the fitting error of the mutation signal.

[0097] The edge of the panoramic video image at multiple resolutions can be regarded as a one-dimensional signal with singularity. The signal formed by the high-frequency and low-frequency subbands is a two-dimensional signal, that is, a plane wave with singularity can be obtained by signal translation.

[0098] Those skilled in the art can understand that after performing wavelet transform on the translation of odd units, the result is the same as the odd-phase sampling value after the original wavelet transform, and the value of performing wavelet transform on the translation of even units is the same as the even-phase sampling value after the original wavelet transform. However, the wavelet coefficients of odd and even phases are very different. Therefore, after performing wavelet processing on an image once, at the boundary of the image plane wave, the high-frequency subband will show an alternating change of large and small coefficients. Performing horizontal wavelet transform within this range will inevitably cause large and small fluctuating coefficients, which will have a certain adverse impact on the coding performance. Further signal processing is required.

[0099] Step 230: Use the one-dimensional wavelet lifting mode for signal processing during the coding process.

[0100] Using the one-dimensional wavelet lifting mode to process the signal mainly includes:

[0101] Transmit the panoramic video image signal a i through the signal index u and split it into two subsets, namely the high-frequency subband index subset and the low-frequency subband index subset, which are respectively represented as:

[0102]

[0103] Use the high-frequency subband index subset to predict the low-frequency subband index subset to obtain the prediction error Δe(u):

[0104]

[0105] In formula (10), represents the predicted low-frequency subband index subset. Combining this prediction error, the high-frequency subband index subset is updated, and the updated high-frequency subband index subset can be expressed as:

[0106]

[0107] In formula (11), θ represents the lifting factor, which is used to control the update amplitude.

[0108] By synthesizing all the update results, the multi-resolution representation result of the original image can be obtained through multiple steps of iteration, thereby completing the lossless coding of the high and low subbands layer by layer.

[0109] The lossless transmission method for panoramic video images at multiple resolutions in the embodiments of the present invention performs translation processing on the original signal when decomposing subband coefficients in different scales and directions using the wavelet function basis to obtain a high and low frequency subband division that can effectively reflect the image edges. At the same time, the one-dimensional wavelet lifting mode is used to effectively improve the quantization accuracy of the high-frequency subband, further ensuring the coding accuracy of image pixels.

[0110] In the actual application process, a comparative test experiment was conducted on the lossless coding performance of the lossless transmission method for panoramic video images at multiple resolutions in the embodiments of the present invention.

[0111] A high-definition video was shot using a DSLR camera. The open OpenCV visual database was used for video data processing. 450 frames of samples were selected as the research target, and the panoramic video images were shot as Figure 3 shown. In Figure 3 (a), the DSLR camera can shoot high-definition video images, which can capture the details of substation equipment and the clarity of the surrounding environment, thus providing more accurate and detailed information. In Figure 3 (b), the pixel arrangement of the captured detail images numbered with 9×9 units is used as an experimental index, and the images that meet this index are regarded as images after effective coding.

[0112] The comparison results of the pixel unit arrangements of the coding algorithm for 6G panoramic video slice division, the coding algorithm based on entropy balance, and the lossless coding algorithm for image transmission at multiple resolutions in the present invention are as Figure 4 shown. In Figure 4 (a), after image coding using the coding algorithm for 6G panoramic video slice division, the edges are blurred, resulting in all edge pixels being of the building pixel type, which does not conform to the actual situation. In Figure 4In (b), when encoding the image using the entropy balance-based encoding algorithm, the multi-resolution problem was not considered, resulting in the pixel unit arrangement not conforming to the actual situation. In Figure 4 In (c), the lossless image transmission encoding algorithm under multi-resolution fully considered the multi-resolution problem, and after image encoding, the Figure 3 same pixel units were obtained.

[0113] To further verify the efficient encoding performance of the studied algorithm, the pixel transmission time consumption of different algorithms is compared as shown in the following table.

[0114]

[0115] The transmission time consumption of using the lossless image transmission encoding algorithm under multi-resolution is the least. When the number of pixels is 300, the transmission time of this algorithm is 50 s, which is lower than other comparison algorithms. Therefore, the performance of the lossless image transmission encoding algorithm under multi-resolution is relatively good.

[0116] An embodiment of the lossless transmission device for panoramic video images under multi-resolution of the present invention includes:

[0117] A memory for storing the program code in the process of the lossless transmission method for panoramic video images under multi-resolution described in the above embodiment;

[0118] A processor for executing the program code in the process of the lossless transmission method for panoramic video images under multi-resolution described in the above embodiment.

[0119] The processor can adopt a DSP (Digital Signal Processor) digital signal processor, an FPGA (Field-Programmable Gate Array) field programmable gate array, an MCU (Microcontroller Unit) system board, a SoC (system on a chip) system board, a PLC (Programmable Logic Controller) minimum system including I / O, or cloud computing power.

[0120] An embodiment of the lossless transmission device for panoramic video images under multi-resolution of the present invention is as Figure 5 shown. In Figure 5 this embodiment includes:

[0121] A coefficient correlation generation module 10 for forming a lossless encoding context signal of the panoramic video image under multi-resolution by using the encoding position correlation of wavelet coefficients;

[0122] The sub-band decomposition generation module 20 is configured to perform wavelet function basis decomposition on the panoramic video image transmission signal after translation processing to form high-frequency and low-frequency sub-bands for compression coding.

[0123] As Figure 5 shown, in an embodiment of the present invention, the coefficient correlation generation module 10 includes:

[0124] The signal quantization unit 11 is configured to form the panoramic video image transmission signal at multiple resolutions;

[0125] The coefficient identification unit 12 is configured to determine the position state between the wavelet coefficients to be encoded of the panoramic video image transmission signal;

[0126] The coefficient correlation unit 13 is configured to form a lossless coding context signal model of the image at multiple resolutions according to the position state between the wavelet coefficients to be encoded.

[0127] As Figure 5 shown, in an embodiment of the present invention, the sub-band decomposition generation module 20 includes:

[0128] The signal translation unit 21 is configured to perform odd signal unit translation on the panoramic video image transmission signal to form a related transmission signal;

[0129] The sub-band decomposition unit 22 is configured to perform wavelet analysis on the panoramic video image transmission signal and the related transmission signal to form a high-frequency sub-band and a low-frequency sub-band;

[0130] The sub-band lifting unit 23 is configured to perform signal processing using a one-dimensional wavelet lifting mode during the coding process.

[0131] As described above, only the preferred specific embodiments of the present invention are provided, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for lossless transmission of panoramic video images at multiple resolutions, characterized in that: include: The coding position correlation of wavelet coefficients is used to form the image lossless coding context signal of panoramic video images at multiple resolutions. The high and low frequency sub-bands for compression coding are formed by performing wavelet function decomposition on the panoramic video image transmission signal after translation processing.

2. The method for lossless transmission of panoramic video images at multiple resolutions according to claim 1, wherein: The method of forming a lossless coding context signal of a panoramic video image at multiple resolutions by utilizing coding position correlation of wavelet coefficients includes: Forming panoramic video image transmission signals at multiple resolutions; Determining the positional state of the wavelet coefficients to be encoded of the panoramic video image transmission signal; A context signal model for lossless image coding at multiple resolutions is formed according to the positional states of the wavelet coefficients to be coded.

3. The method for lossless transmission of panoramic video images at multiple resolutions according to claim 2, wherein: The position status between the wavelet coefficients to be coded includes the brother nodes of the wavelet coefficients to be coded in the same coding layer in the horizontal, vertical and diagonal directions or The brother nodes of the wavelet coefficient to be coded in the horizontal, vertical and diagonal directions on the same coding layer and the parent node of the previous coding layer.

4. The method for lossless transmission of panoramic video images at multiple resolutions according to claim 2, wherein: When the multi-resolution image lossless coding context signal has no parent node: When the wavelet coefficients to be coded A(x,y) are in the horizontal or vertical layer to be coded, the context signal model for lossless coding of images at multiple resolutions is expressed as: Where ζ represents the context quantization operator; A(x,y) represents the wavelet coefficient to be coded with x as the horizontal coordinate and y as the vertical coordinate; h x 、k y Represents the encoding information in the horizontal or vertical direction respectively; When the wavelet coefficients to be coded A(x,y) are in the diagonal layer to be coded, the context signal model for lossless coding of the image at multiple resolutions is expressed as:

5. The method for lossless transmission of panoramic video images at multiple resolutions according to claim 2, wherein: When the multi-resolution image lossless coding context signal has a parent node: When the coefficient to be coded A(x,y) is in the horizontal or vertical layer to be coded, the context signal model for lossless coding of the image at multiple resolutions is expressed as: in, represents the context quantization operator; A(x,y) represents the wavelet coefficient to be coded with the horizontal coordinate x and the vertical coordinate y; h x 、k y Represents the encoding information in the horizontal or vertical direction respectively; When the coefficient to be coded A(x,y) is in the diagonal layer to be coded, the context signal model for lossless coding of the image at multiple resolutions is expressed as:

6. The method for lossless transmission of panoramic video images at multiple resolutions according to claim 1, wherein: The method of forming high and low frequency sub-bands for compression coding by performing wavelet function basis decomposition on the panoramic video image transmission signal after the translation processing includes: Performing odd-number signal unit shifting on the panoramic video image transmission signal to form a related transmission signal; Performing wavelet analysis on the panoramic video image transmission signal and the related transmission signal to form high-frequency sub-bands and low-frequency sub-bands; During the encoding process, one-dimensional wavelet lifting mode is used for signal processing.

7. The method for lossless transmission of panoramic video images at multiple resolutions according to claim 6, wherein: The high-frequency and low-frequency sub-bands are: Among them, γ represents the downsampling operator; ι represents the translation operator; w ai represents the lossless coding context; η a ,η b Represent the wavelet function basis of high-frequency and low-frequency sub-bands respectively.

8. The method for lossless transmission of panoramic video images at multiple resolutions according to claim 6, wherein: The one-dimensional wavelet lifting mode processing signal mainly includes: Transmit the panoramic video image to signal a through signal index u i Split into two subsets, namely the high-frequency subband index subset and the low-frequency subband index subset, respectively expressed as: Use the high-frequency subband index subset to predict the low-frequency subband index subset and obtain the prediction error Δe(u): in, Represents the predicted low-frequency subband index subset; Combined with the prediction error, the high-frequency subband index subset is updated, and the updated high-frequency subband index subset can be expressed as: Among them, θ represents the boost factor, which is used to control the update amplitude.

9. A device for lossless transmission of panoramic video images at multiple resolutions, characterized in that: include: A memory for storing program codes in a process of processing the method for lossless transmission of panoramic video images at multiple resolutions according to any one of claims 1 to 8; A processor is configured to execute the program code.

10. A device for lossless transmission of panoramic video images at multiple resolutions, characterized in that: include: A coefficient correlation generation module is used to form a context signal for lossless coding of a panoramic video image at multiple resolutions by utilizing the coding position correlation of the wavelet coefficients; The sub-band decomposition generation module is used to form high and low frequency sub-bands for compression coding by performing wavelet function basis decomposition on the panoramic video image transmission signal after the translation processing.

Images