A method and device for lossless transmission of panoramic video images at multiple resolutions

Abstract

The application provides a kind of multi-resolution panorama video image lossless transmission method and device, solve the technical problems of performance conflict between existing video image transmission code stream and image quality.Method includes: using the coding position correlation of wavelet coefficient to form the image lossless coding context signal of panorama video image under multi-resolution;Through wavelet function base decomposition to the panorama video image transmission signal after translation processing, form high-low frequency sub-band for compression coding.By decomposing panorama video image into components under different resolutions, and using wavelet function base to sparsely represent and losslessly encode each component, the efficient transmission of multi-resolution image is realized.The algorithm has high transmission efficiency and high image quality advantage, and provides a new idea for the development of panorama video image transmission field.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, and in particular to a panorama video image lossless transmission method and device under multi-resolution. BACKGROUND

[0002] With the development of emerging technologies such as virtual reality (VR) and augmented reality (AR), the demand for panorama video image transmission is increasing. Panorama video images are challenging in real-time transmission and storage due to their high resolution, large amount of data, and high requirements for transmission speed. Traditional lossless encoding algorithms often struggle to meet real-time transmission requirements while ensuring image quality. Therefore, developing an efficient panorama video image lossless encoding algorithm is of great significance to meet the demand for high-quality image transmission in future virtual reality applications. In the prior art, the encoding algorithm for 6G panorama video slice division divides the input panorama video into multiple segments according to the scene content, encodes each segment, and uses appropriate encoding algorithms to compress the video segments to reduce the data volume. During the encoding process, the algorithm optimizes the content and quality of the video segments to maintain the original quality and visual effect of the image. The entropy-balanced encoding algorithm encodes each macroblock and adjusts adaptively according to network bandwidth and device performance to achieve more efficient video transmission and playback. The lossless encoding algorithm based on Walsh-Hadmard butterfly transform preprocesses the input image and divides it into multiple subblocks. The image is converted from the spatial domain to the transform domain, where the energy concentration of the image is higher, so better lossless encoding can be achieved. However, the above three algorithms require a large amount of context information when processing high-resolution panorama images, resulting in high computational complexity and poor real-time performance.

[0003] In the prior art, wavelet transform is a signal processing technique that can decompose an image into subband coefficients at different scales and directions. These coefficients reflect the information of the image at different frequencies and positions. By quantizing and encoding the subband coefficients, image compression can be achieved. The quantization process usually involves retaining larger coefficients and discarding smaller coefficients to reduce data volume, which can achieve higher compression efficiency and image quality. However, it is mainly used for compression processing of single-resolution static images, such as the encoding system of JPEG 2000. SUMMARY

[0004] In view of the above problems, the embodiments of the present application provide a panorama video image lossless transmission method and device under multi-resolution, which solves the technical problem of performance conflict between existing video image transmission code stream and image quality.

[0005] The panorama video image lossless transmission method under multi-resolution of the embodiments of the present application comprises:

[0006] The coding position correlation of wavelet coefficients is used to form an image lossless coding context signal of the panoramic video image under multi-resolution;

[0007] The high and low frequency subbands for compression coding are formed by wavelet function base decomposition of the panoramic video image transmission signal after the translation processing.

[0008] In an embodiment of the present application, the coding position correlation of wavelet coefficients is used to form an image lossless coding context signal of the panoramic video image under multi-resolution, comprising:

[0009] The panoramic video image transmission signal under multi-resolution is formed;

[0010] The position state between the wavelet coefficients to be coded of the panoramic video image transmission signal is determined;

[0011] The image lossless coding context signal model under multi-resolution is formed according to the position state between the wavelet coefficients to be coded.

[0012] In an embodiment of the present application, the position state between the wavelet coefficients to be coded comprises the sibling nodes of the wavelet coefficients to be coded in the horizontal, vertical and diagonal directions of the same coding layer level, or

[0013] The sibling nodes of the wavelet coefficients to be coded in the horizontal, vertical and diagonal directions of the same coding layer level and the parent node of the last coding layer.

[0014] In an embodiment of the present application, when the image lossless coding context signal under multi-resolution has no parent node, the image lossless coding context signal model under multi-resolution is represented as:

[0015] When the wavelet coefficient A(x, y) to be coded is in the horizontal or vertical direction of the coding layer to be coded, the image lossless coding context signal model under multi-resolution is represented as:

[0016]

[0017] Wherein, The context quantization operator is represented; A(x, y) represents the wavelet coefficient to be coded in the horizontal coordinate x and the vertical coordinate y; h x , k y respectively represent the coding information in the horizontal or vertical direction.

[0018] When the wavelet coefficient A(x, y) to be coded is in the diagonal direction of the coding layer to be coded, the image lossless coding context signal model under multi-resolution is represented as:

[0019]

[0020] In an embodiment of the present application, when the image lossless coding context signal under multi-resolution has a parent node, the image lossless coding context signal model under multi-resolution is represented as:

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

[0022]

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

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

[0025]

[0026] In an embodiment of the present application, the high-frequency and low-frequency subbands for compression coding are formed by wavelet function base decomposition on the panoramic video image transmission signal after translation processing, and the method comprises the following steps:

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

[0028] The wavelet analysis is performed on the panoramic video image transmission signal and the related transmission signal to form a high-frequency subband and a low-frequency subband;

[0029] A one-dimensional wavelet lifting mode is used for signal processing in the coding process.

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

[0031]

[0032] Wherein, γ represents a down-sampling operator; ι represents a translation operator; represents a 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 application, the one-dimensional wavelet lifting mode processes the signal, and mainly comprises:

[0034] The panoramic video image transmission signal a i is split into two subsets, which are a high-frequency subband index subset and a low-frequency subband index subset, and are respectively expressed as:

[0035]

[0036] The low-frequency sub-band index subset is predicted using a high-frequency sub-band index subset, and a prediction error Δe(u) is obtained:

[0037]

[0038] wherein, represents the predicted low-frequency sub-band index subset;

[0039] The high-frequency sub-band index subset is updated in combination with the prediction error, and the updated high-frequency sub-band index subset can be represented as:

[0040]

[0041] wherein, θ represents a lifting factor, used for controlling the updating amplitude.

[0042] The multi-resolution panoramic video image lossless transmission device of the embodiment of the application comprises:

[0043] The memory is used for storing program codes in the process of the multi-resolution panoramic video image lossless transmission method according to any one of claims 1 to 8.

[0044] The processor is used for executing the program codes.

[0045] The multi-resolution panoramic video image lossless transmission device of the embodiment of the application comprises:

[0046] The coefficient correlation generation module is used for forming an image lossless coding context signal of the panoramic video image in the multi-resolution by using the coding position correlation of the wavelet coefficients.

[0047] The sub-band decomposition generation module is used for forming high and low frequency sub-bands used for compression coding by wavelet function base decomposition on the panoramic video image transmission signal after the translation processing.

[0048] The multi-resolution panoramic video image lossless transmission method and device of the embodiment of the application realize the efficient transmission of the multi-resolution image by decomposing the panoramic video image into components in different resolutions and using the wavelet function base to perform sparse representation and lossless coding on each component. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 Fig. 1 shows a flowchart of the multi-resolution panoramic video image lossless transmission method of the embodiment of the application.

[0050] Figure 2The figure shows the relevant position of the wavelet coefficient to be coded in the lossless coding context model of the multi-resolution panoramic video image lossless transmission method according to an embodiment of the application.

[0051] Figure 3 The figure shows the local details of the original panoramic video image in the application process of the multi-resolution panoramic video image lossless transmission method according to an embodiment of the application.

[0052] Figure 4 The figure shows the comparison of the coding pattern recovered after processing by each compression coding method in the application process of the multi-resolution panoramic video image lossless transmission method according to an embodiment of the application.

[0053] Figure 5 The figure shows the architecture of the multi-resolution panoramic video image lossless transmission device according to an embodiment of the application. DETAILED DESCRIPTION

[0054] To make the objectives, technical solutions, and advantages of the present application clearer and more comprehensible, the present application is further described below in conjunction with the drawings and specific embodiments. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0055] The multi-resolution panoramic video image lossless transmission method according to an embodiment of the application is shown in the figure. Figure 1 In the figure, the embodiment includes: Figure 1

[0056] Step 100: Form the image lossless coding context signal of the panoramic video image in the multi-resolution by using the coding position correlation of the wavelet coefficient.

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

[0058] Based on the panoramic video image transmission signal in the multi-resolution, the wavelet coefficients are used to form the correlation relationship, and the state probability of each variable is estimated. The importance of the wavelet coefficient is closely related to the importance of the adjacent coefficient, and is also closely related to the importance of the same level child node and the upper level child node in the same level. ​

[0059] By using image information at different resolutions, the image is more effectively compressed, thereby reducing the size of data and improving the compression efficiency. Further using the correlation of wavelet coefficients for constructing the lossless encoding context signal of the image, the lossless encoding is not easy to be tampered, and the security of image transmission can be enhanced.

[0060] Step 200: forming high-frequency subbands and low-frequency subbands for compression coding by wavelet function base decomposition of the panoramic video image transmission signal after translation processing.

[0061] The wavelet function base can decompose the signal into components of different frequencies. The wavelet function base has the sparse coding property, and can decompose the signal into a small number of wavelet coefficients, and most of the wavelet coefficients are almost 0. Since the coding context signal contains noise and redundant information, this sparse representation can separate the abrupt part and the noise part in the signal, thereby reducing the fitting error of the abrupt signal.

[0062] By decomposing the correlation signal formed by translation processing of the same image lossless encoding context signal into high-frequency subbands and low-frequency subbands by different wavelet function bases, and corresponding subband coefficients, the change of the subband coefficients reflects the coefficient fluctuation of the panoramic video image at the image edge under multi-resolution. Further, layer-by-layer lossless encoding compression of the high-frequency and low-frequency subbands is formed.

[0063] The multi-resolution panoramic video image lossless transmission method of the embodiment of the present application decomposes the panoramic video image into components at different resolutions, and uses the wavelet function base to perform sparse representation and lossless encoding on each component, thereby realizing efficient transmission of multi-resolution images. The algorithm has the advantages of high transmission efficiency and high image quality, and provides a new technical idea for the development of the panoramic video image transmission field.

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

[0065] Step 110: forming a multi-resolution panoramic video image transmission signal.

[0066] Let θ i be the resolution 2 i approximation of the space function, then the resolution under i+1 can be represented as:

[0067]

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

[0069] Let g i be the resolution 2​i The orthogonal projection operator on the plane The panoramic video image transmission signal at the resolution of 2 i The panoramic video image transmission signal at the resolution of 2

[0070]

[0071] In formula (2), the initial signal is represented by

[0072] Step 120: determining the position state among the to-be-encoded wavelet coefficients of the panoramic video image transmission signal.

[0073] Based on the panoramic video image transmission signal a i at the multi-resolution, the correlation relationship of the wavelet coefficients is used to estimate the variable state probability. The importance of the wavelet coefficients is closely related to the importance of the adjacent coefficients, and is also closely related to the importance of the same level child nodes and the superior child nodes at the same level.

[0074] The relevant positions of the to-be-encoded wavelet coefficients are shown in Figure 2 In Figure 2 C a , C b and C d respectively represent the sibling nodes of the to-be-encoded wavelet coefficient A at the same coding layer level, vertical and diagonal directions; O represents the parent node of the to-be-encoded wavelet coefficient A at the previous coding layer.

[0075] The importance conditions of the neighborhood pixels of the to-be-encoded wavelet coefficient 8, the importance conditions of the sibling nodes and the parent node jointly constitute an information expression which is independent of the event relationship. Through adaptive selection of the sub-frequency band to which the to-be-encoded wavelet coefficient belongs, adaptive selection of the sibling nodes is realized. According to the different coding layer positions of the to-be-encoded wavelet coefficient, the coding context construction is divided into two cases, that is, case one of the to-be-encoded wavelet coefficient A(x, y) without a parent node and case two of the to-be-encoded wavelet coefficient A(x, y) with a parent node.

[0076] Step 130: forming the image lossless coding context signal model at the multi-resolution according to the position state among the to-be-encoded wavelet coefficients.

[0077] In case one (the to-be-encoded wavelet coefficient A(x, y) without a parent node):

[0078] When the to-be-encoded wavelet coefficient A(x, y) is in the to-be-encoded layer in the horizontal or vertical direction, the image lossless coding context signal model at the multi-resolution is represented as:

[0079]

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

[0081] When the to-be-encoded wavelet coefficient A(x, y) is in the to-be-encoded layer in the diagonal direction, the image lossless coding context signal model under multi-resolution is represented as:

[0082]

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

[0084] When the to-be-encoded coefficient A(x, y) is in the to-be-encoded layer in the horizontal or vertical direction, the image lossless coding context signal model under multi-resolution is represented as:

[0085]

[0086] When the to-be-encoded coefficient A(x, y) is in the to-be-encoded layer in the diagonal direction, the image lossless coding context signal model under multi-resolution is represented as:

[0087]

[0088] The panoramic video image lossless transmission method under multi-resolution in the embodiment of the application can effectively compress the image by forming the image lossless coding context signal model under multi-resolution and using the image information under different resolutions, thereby reducing the size of data and improving the compression efficiency. The image lossless coding context signal model is constructed, so that the lossless coding is not easy to be tampered with, and thus the security of image transmission can be enhanced.

[0089] As Figure 1 shown, in an embodiment of the application, the step 200 comprises:

[0090] Step 210: shifting the panoramic video image transmission signal by an odd number of signal units to form a correlation transmission signal.

[0091] The panoramic video image transmission signal a i The correlation transmission signal is formed by shifting the panoramic video image transmission signal by an odd number of units, and the frequency components of the two signals are different in positive and negative directions, so that wavelet analysis of two different frequencies of the same signal can be formed.

[0092] Step 220: performing wavelet analysis on the panoramic video image transmission signal and the correlation transmission signal to form a high-frequency subband and a low-frequency subband.

[0093] The correlation transmission signal is formed by shifting the panoramic video image transmission signal by an odd number of units, and the frequency components of the two signals are different in positive and negative directions, so that wavelet analysis of two different frequencies of the same signal can be formed.i The translation of odd number of units is formed. The calculation formula of high frequency and low frequency sub-band is:

[0094]

[0095] In formula (7), γ represents a down-sampling operator; ι represents a translation operator; η a η b respectively represent wavelet function bases of high frequency and low frequency sub-band.

[0096] Since the noise and redundant information are contained in the coding context, the signal can be decomposed into components of different frequencies by using the wavelet function base. The wavelet function base has the sparse coding property, 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 abrupt change part and the noise part in the signal, thereby reducing the fitting error of the abrupt change signal.

[0097] The edge of the panoramic video image in multi-resolution can be regarded as a one-dimensional signal with singularity. The signal formed by high frequency and low frequency sub-band 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 wavelet transform is performed on the odd number of unit translation, the result is the same as the odd phase sampling value after original wavelet transform, and the value of the even number of unit translation after wavelet transform is the same as the even phase sampling value after original wavelet transform. The wavelet coefficients of odd and even phases are quite different. Therefore, after wavelet processing is performed on an image, the high frequency sub-band will appear alternating changes of large and small coefficients at the boundary of the image plane wave. When horizontal direction wavelet transform is performed in this range, large and small wave coefficients will inevitably be caused, which further causes certain adverse effects on the performance of coding. Further signal processing is needed.

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

[0100] The signal is processed by using one-dimensional wavelet lifting mode, mainly including:

[0101] The panoramic video image transmission signal a i is split into two subsets, which are high frequency sub-band index subset and low frequency sub-band index subset, and are respectively represented as:

[0102]

[0103] The low frequency sub-band index subset is predicted by using the high frequency sub-band index subset, and the prediction error Δe(u) is obtained:

[0104]

[0105] In formula (10), This represents the predicted low-frequency subband index subset. Based on this prediction error, the high-frequency subband index subset is updated, resulting in the updated high-frequency subband index subset, which can be represented as:

[0106]

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

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

[0109] The lossless transmission method for panoramic video images under multiple resolutions in this invention performs translation processing on the original signal when decomposing subband coefficients at different scales and directions using wavelet function basis to obtain high- and low-frequency subband divisions that can effectively reflect image edges. Simultaneously, the one-dimensional wavelet lifting mode effectively improves the quantization accuracy of the high-frequency subbands, further ensuring the encoding accuracy of image pixels.

[0110] In practical applications, comparative tests were conducted on the lossless coding performance of the lossless transmission method for panoramic video images under multiple resolutions according to embodiments of the present invention.

[0111] High-definition video was captured using a DSLR camera. The open visual database OpenCV was used for video data processing. A sample of 450 frames was selected as the research objective, and panoramic video images were obtained, such as... Figure 3 As shown. In Figure 3 In (a), the DSLR camera can capture high-definition video images, capturing details of substation equipment and the clarity of the surrounding environment, thus providing more accurate and detailed information. Figure 3 In (b), the pixel arrangement of the captured detail images using 9×9 unit numbering is used as the experimental index, and images that meet this index are considered as valid encoded images.

[0112] The comparison results of pixel unit arrangement of the encoding algorithm for 6G panoramic video segmentation, the encoding algorithm based on entropy balance, and the lossless image transmission encoding algorithm under multi-resolution of this invention are as follows: Figure 4 As shown. In Figure 4 In (a), the encoding algorithm used for 6G panoramic video segmentation results in blurred edges after image encoding, causing edge pixels to be classified as building pixels, which is inconsistent with reality. Figure 4In (b), when the image is encoded using the encoding algorithm based on the entropy balance, the multi-resolution problem is not considered, resulting in that the pixel unit arrangement is inconsistent with the actual one. Figure 4 In (c), the multi-resolution image transmission lossless encoding algorithm fully considers the multi-resolution problem, and the pixel unit obtained after image encoding is consistent with the actual one. Figure 3

[0113] In order to further verify the high encoding performance of the studied algorithm, the pixel transmission time consumption of different algorithms is compared in the following table.

[0114]

[0115] The transmission time consumption of the multi-resolution image transmission lossless encoding algorithm is the least, and when the number of pixels is 300, the transmission time of the algorithm is 50s, which is lower than that of other comparative algorithms. Therefore, the performance of the multi-resolution image transmission lossless encoding algorithm is better.

[0116] An embodiment of the multi-resolution panoramic video image lossless transmission device of the present application comprises:

[0117] The memory is used for storing the program code in the process of the multi-resolution panoramic video image lossless transmission method of the above embodiment.

[0118] The processor is used for executing the program code in the process of the multi-resolution panoramic video image lossless transmission method of the above embodiment.

[0119] The processor can adopt a digital signal processor (DSP), a field-programmable gate array (FPGA), a microcontroller unit (MCU) system board, a system on a chip (SoC), a programmable logic controller (PLC) minimum system including I / O or cloud computing power.

[0120] An embodiment of the multi-resolution panoramic video image lossless transmission device of the present application is shown in Figure 5 In the embodiment, the present embodiment comprises: Figure 5

[0121] The coefficient correlation generation module 10 is used for forming the multi-resolution image lossless encoding context signal of the panoramic video image by using the encoding position correlation of the wavelet coefficient.

[0122] ​​The sub-band decomposition generating module 20 is used to form high and low frequency sub-bands for compression coding by wavelet function base decomposition of the panorama video image transmission signal after the shift processing.

[0123] As shown in the figure, in an embodiment of the present application, the coefficient correlation generating module 10 comprises: Figure 5

[0124] The signal quantization unit 11 is used to form the panorama video image transmission signal under multi-resolution;

[0125] The coefficient identification unit 12 is used to determine the position state among the wavelet coefficients to be coded of the panorama video image transmission signal;

[0126] The coefficient correlation unit 13 is used to form the image lossless coding context signal model under multi-resolution according to the position state among the wavelet coefficients to be coded.

[0127] As shown in the figure, in an embodiment of the present application, the sub-band decomposition generating module 20 comprises: Figure 5

[0128] The signal shift unit 21 is used to shift the panorama video image transmission signal by odd signal unit to form a related transmission signal;

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

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

[0131] The above description is only the preferred embodiment of the present application, but the protection scope of the present application is not limited to this. Any change or replacement within the technical range disclosed by the present application can be easily thought by those skilled in the art, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.​​

Claims

1. A method for lossless transmission of panoramic video images under multiple resolutions, characterized in that, include: The coding position correlation of wavelet coefficients is used to form the lossless coding context signal of panoramic video images at multiple resolutions; High and low frequency subbands for compression coding are formed by decomposing the transmitted signal of the panoramic video image after translation processing using wavelet function basis decomposition. The generation of the panoramic video image transmission signal includes: set up For resolution For the approximation of a space function, then in The resolution below is: （1） in, Indicates the first indivual exist Orthogonal complement at resolution; set up For resolution hour The orthogonal projection operator on the resolution is then used at a resolution of The panoramic video image transmission signal at that time is: （2） in, This represents the initial signal.

2. The method for lossless transmission of panoramic video images under multiple resolutions as described in claim 1, characterized in that, The method of generating lossless encoding context signals for panoramic video images at multiple resolutions using the coding position correlation of wavelet coefficients includes: To generate panoramic video image transmission signals at multiple resolutions; Determine the positional state between the wavelet coefficients to be encoded in the panoramic video image transmission signal; A lossless image coding context signal model at multiple resolutions is formed based on the positional state between the wavelet coefficients to be encoded.

3. The method for lossless transmission of panoramic video images under multiple resolutions as described in claim 2, characterized in that, The positional state between the wavelet coefficients to be encoded includes the sibling nodes of the wavelet coefficients in the same coding layer in the horizontal, vertical, and diagonal directions. The wavelet coefficients to be encoded are the sibling nodes in the horizontal, vertical, and diagonal directions of the same coding layer and the parent node of the previous coding layer.

4. The method for lossless transmission of panoramic video images under multiple resolutions as described in claim 2, characterized in that, When the lossless encoding context signal for images under multi-resolution has no parent node: When the wavelet coefficients to be encoded In the layer to be encoded in the horizontal or vertical direction, the lossless encoding context signal model of the image at multiple resolutions is represented as: in, Indicates the context quantization operator; Indicates that the x-axis is The vertical axis is The wavelet coefficients to be encoded; , These represent encoded information in the horizontal or vertical directions, respectively. When the wavelet coefficients to be encoded In the diagonal layers to be encoded, the lossless encoding context signal model for images at multiple resolutions is represented as follows: Among them, C a C b These represent sibling nodes of wavelet coefficients in the same coding layer, in the horizontal and vertical directions, respectively. Transmit signals for panoramic video images.

5. The method for lossless transmission of panoramic video images under multiple resolutions as described in claim 2, characterized in that, When the lossless image coding context signal under multi-resolution has a parent node: When the coefficients to be encoded In the layer to be encoded in the horizontal or vertical direction, the lossless encoding context signal model of the image at multiple resolutions is represented as: in, Indicates the context quantization operator; Indicates that the x-axis is The vertical axis is The wavelet coefficients to be encoded; , These represent encoded information in the horizontal or vertical directions, respectively. When the coefficients to be encoded In the diagonal layers to be encoded, the lossless encoding context signal model for images at multiple resolutions is represented as follows: Among them, C a C b These represent sibling nodes of wavelet coefficients in the same coding layer in the horizontal and vertical directions, respectively, while O represents the parent node of the wavelet coefficient in the previous coding layer. Transmit signals for panoramic video images.

6. The method for lossless transmission of panoramic video images under multiple resolutions as described in claim 1, characterized in that, The step 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 translation processing includes: The panoramic video image transmission signal is translated by an odd number of signal units to form a related transmission signal; Wavelet analysis is performed on the panoramic video image transmission signal and related transmission signal to form high-frequency sub-bands and low-frequency sub-bands; One-dimensional wavelet lifting mode is used for signal processing during the encoding process.

7. The method for lossless transmission of panoramic video images under multiple resolutions as described in claim 6, characterized in that, The high-frequency and low-frequency sub-bands are: in, Indicates the downsampling operator; Represents the translation operator; Indicates the lossless coding context; , These represent the wavelet function bases for the high-frequency and low-frequency subbands, respectively. Transmit signals for panoramic video images.

8. The method for lossless transmission of panoramic video images under multiple resolutions as described in claim 6, characterized in that, The one-dimensional wavelet lifting mode processes signals, mainly including: By signal index Transmit panoramic video images as signals It is split into two subsets: the high-frequency subband index subset and the low-frequency subband index subset, represented as follows: ； Predicting the low-frequency subband index subset using the high-frequency subband index subset yields the prediction error. : in, This indicates a subset of the predicted low-frequency subband index; Based on the prediction error, the high-frequency subband index subset is updated, and the updated high-frequency subband index subset can be represented as: in, This represents the boost factor, used to control the update magnitude.

9. A lossless transmission device for panoramic video images under multiple resolutions, characterized in that, include: The memory is used to store program code during the processing of the lossless transmission method for panoramic video images under multiple resolutions as described in any one of claims 1 to 8; A processor for executing the program code.

10. A lossless transmission device for panoramic video images under multiple resolutions, characterized in that, include: The coefficient correlation generation module is used to generate lossless coding context signals for panoramic video images at multiple resolutions by utilizing the coding position correlation of 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 transmission signal of the panorama video image after translation processing. The generation of the panoramic video image transmission signal includes: set up For resolution For the approximation of a space function, then in The resolution below is: （1） in, Indicates the first indivual exist Orthogonal complement at resolution; set up For resolution hour The orthogonal projection operator on the resolution is then used at a resolution of The panoramic video image transmission signal at that time is: （2） in, This represents the initial signal.

Images