CN109561314B - Self-adaptive template prediction method for bandwidth compression - Google Patents
Self-adaptive template prediction method for bandwidth compression Download PDFInfo
- Publication number
- CN109561314B CN109561314B CN201811261682.6A CN201811261682A CN109561314B CN 109561314 B CN109561314 B CN 109561314B CN 201811261682 A CN201811261682 A CN 201811261682A CN 109561314 B CN109561314 B CN 109561314B
- Authority
- CN
- China
- Prior art keywords
- adaptive
- current
- adaptive template
- reference direction
- reconstruction value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 230000006835 compression Effects 0.000 title claims abstract description 15
- 238000007906 compression Methods 0.000 title claims abstract description 15
- 230000003044 adaptive effect Effects 0.000 claims abstract description 75
- 230000009191 jumping Effects 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/182—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a pixel
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/48—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using compressed domain processing techniques other than decoding, e.g. modification of transform coefficients, variable length coding [VLC] data or run-length data
Abstract
The invention relates to a bandwidth compression self-adaptive template prediction method, which comprises the following steps: step 1, defining the number of epitopes and the serial numbers of the epitopes of a self-adaptive template; step 2, updating the adaptive template list according to the MB reconstruction value of the adjacent reference direction of the current MB; step 3, predicting the current MB and the MB reconstruction value in the adaptive template list by the adaptive texture to obtain the prediction residual error of the current MB; step 4, judging whether all MB prediction residual errors are obtained or not, if so, ending the prediction; otherwise, jumping to step 2. According to the invention, the self-adaptive template is defined, and the predicted pixel value of the current predicted macro block is calculated.
Description
Technical Field
The invention relates to the technical field of compression, in particular to a self-adaptive template prediction method for bandwidth compression.
Background
Today, with the rapid development of communication technology, multimedia is integrated into the life and work of people. With the conversion of video from analog to digital, people have higher and higher requirements on definition, fluency and real-time degree of video quality, and the video compression technology becomes an important link for solving the problem. The digital video information has huge data volume, and can occupy huge storage space and channel bandwidth, thereby restricting the expansion of the video communication industry. In a channel with limited bandwidth, the compression coding technology is adopted to reduce the transmission data volume, which is an important means for improving the communication speed. In view of the present situation and future development trend of multimedia communication, it is still the only way to store and transmit digitized video information in compressed form for a long time.
The video images occupy more and more storage space and transmission bandwidth. On the basis of conventional video compression, it is becoming more and more important to improve the storage space and transmission bandwidth of images by using on-chip bandwidth compression technology. The bandwidth compression technology consists of a prediction module, a quantization module, a code control module and an entropy coding module; the prediction module predicts the current pixel value according to the adjacent pixel information by utilizing the spatial redundancy existing between the adjacent pixels, and the standard deviation of the prediction difference value is far smaller than that of the original image data, so that the prediction difference value is encoded, the theoretical entropy of the image data is more favorably minimized, and the purpose of improving the compression efficiency is achieved. The algorithms of the current prediction module are mainly divided into two types, namely texture related prediction and pixel value related prediction.
However, when the texture of the image to be compressed is complex and changeable, the prediction coding cannot be accurately referred due to poor correlation between image textures when predicting the complex texture area of the image to be compressed, so that the theoretical limit entropy cannot be maximally reduced, and the quality of a prediction module is affected. Therefore, when the texture of the image to be compressed is complicated and variable, improving the quality of the prediction module becomes an urgent problem to be solved.
Disclosure of Invention
Therefore, in order to solve the technical defects and shortcomings in the prior art, the invention provides a bandwidth compression adaptive template prediction method.
Specifically, an embodiment of the present invention provides an adaptive template prediction method for bandwidth compression, including:
and 5, calculating the prediction residual of the current MB according to the reference pixel.
In one embodiment of the present invention, step 1 comprises:
step 11, defining the number and serial number of the epitopes of the adaptive template list; wherein, the smaller the epitope sequence number, the higher the priority level;
and step 12, initializing and filling the adaptive template list.
In one embodiment of the present invention, the number of the epitopes is N, the epitope numbers are 0 to N-1, and each of the epitopes is initialized to be filled with a set of reconstruction values of one MB.
In one embodiment of the present invention, the step 2 comprises:
detecting whether the reconstruction value of the MB in the adjacent reference direction of the current MB is consistent with the reconstruction value filled in the adaptive template list or not, and if so, exchanging the consistent reconstruction value with the reconstruction value of the epitope serial number corresponding to the adaptive template list; otherwise, the reconstruction value of the MB in the adjacent reference direction is filled into the epitope serial number corresponding to the adaptive template list.
In one embodiment of the invention, the neighboring reference direction comprises an upper neighboring reference direction, a left neighboring reference direction, an upper left neighboring reference direction or an upper right neighboring reference direction.
In an embodiment of the present invention, the serial number of the epitope corresponding to the upper adjacent reference direction is 0; the epitope serial number corresponding to the left adjacent reference direction is 1; the serial number of the epitope corresponding to the upper left adjacent reference direction is 2; and the serial number of the epitope corresponding to the upper right adjacent reference direction is 3.
In one embodiment of the present invention, the step 3 comprises: and matching the pixel value of the current MB with the reconstruction value of each MB in the list of the adaptive templates, and selecting at least one group of reconstruction values as candidate reconstruction values.
In one embodiment of the present invention, the step 4 comprises: and carrying out adaptive texture prediction on the pixel value of the current MB and the candidate reconstruction value to obtain a reference pixel of the current MB.
Based on this, the invention has the following advantages:
the invention has the following beneficial effects: compared with the prior art, when the texture of the image to be compressed is complex, different texture regions corresponding to different adaptive template lists are defined, the probability of matching the pixels in the current MB with the pixels of the selected candidate reconstruction values in the adaptive template list is easier to improve, the precision of solving the prediction residual value of the complex texture regions can be improved, the theoretical limit entropy is further reduced, and the bandwidth compression ratio is increased.
Drawings
The following detailed description of embodiments of the invention will be made with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for adaptive template prediction according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a list of adaptive templates according to an embodiment of the present invention;
FIG. 3 is a flow chart of another adaptive template prediction method according to an embodiment of the present invention;
fig. 4 is a schematic diagram of adaptive texture prediction neighboring reference pixels according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Example one
Referring to fig. 1, fig. 1 is a flowchart of an adaptive template prediction method according to an embodiment of the present invention, where the method includes the following steps:
and 5, calculating the prediction residual of the current MB according to the reference pixel.
Specifically, step 1 may include:
step 11, defining the number and serial number of the epitopes of the adaptive template list; wherein, the smaller the epitope sequence number, the higher the priority level;
and step 12, initializing and filling the adaptive template list.
Furthermore, the number of the epitopes is N, the serial numbers of the epitopes are 0 to N-1, and each epitope is initialized and filled with a group of reconstruction values of an MB; wherein, N can be 4, 8, 16 or 32, etc.
Further, the step 2 may include:
detecting whether the reconstruction value of the MB in the adjacent reference direction of the current MB is consistent with the reconstruction value filled in the adaptive template list or not, and if so, exchanging the consistent reconstruction value with the reconstruction value of the epitope serial number corresponding to the adaptive template list; otherwise, the reconstruction value of the MB in the adjacent reference direction is filled into the epitope serial number corresponding to the adaptive template list.
Preferably, the adjacent reference direction comprises an upper adjacent reference direction, a left adjacent reference direction, an upper left adjacent reference direction or an upper right adjacent reference direction.
Specifically, the serial number of the epitope corresponding to the upper adjacent reference direction is 0; the epitope serial number corresponding to the left adjacent reference direction is 1; the serial number of the epitope corresponding to the upper left adjacent reference direction is 2; and the serial number of the epitope corresponding to the upper right adjacent reference direction is 3.
Further, the step 3 may include: and matching the pixel value of the current MB with the reconstruction value of each MB in the list of the adaptive templates, and selecting the reconstruction value of at least one epitope as a candidate reconstruction value.
Wherein, the rdo formula for selecting the candidate reconstruction value is as follows:
where Cur is the original pixel value of the current MB, Pred is the reconstruction value filled by any one of the epitopes in the adaptive template list, and i isThe epitope sequence number corresponding to Pred; MBnum is the number of pixels in the current MB, c1And c2Is a weight coefficient; the smaller the finally calculated rdo is, the better the corresponding reconstruction value in the adaptive template list is, and the optimal reconstruction value is selected as a candidate reconstruction value.
Further, the values of c1 and c2 can be preset fixed values; for convenience of calculation, c1 may be set to 1 and c2 may be set to 0 directly.
Specifically, the step 4 includes: and carrying out adaptive texture prediction on the pixel value of the current MB and the candidate reconstruction value to obtain a reference pixel of the current MB.
Specifically, the prediction residual is the pixel value of the current MB minus the pixel value of the reference pixel.
According to the self-adaptive template prediction method provided by the embodiment, a self-adaptive template list is defined, a template is extracted from an original image in a self-adaptive manner, a reference pixel is selected for a current pixel according to the template, and then a prediction residual error is calculated, so that the problem of how to improve the quality of a prediction module when the texture of an image to be compressed is complex and changeable is solved; by adopting the adaptive template prediction method provided by the embodiment, the theoretical limit entropy can be further reduced for the complex texture sequence.
Example two
Referring to fig. 2, fig. 2 is a schematic diagram of an adaptive template list according to an embodiment of the present invention. The present embodiment describes another adaptive template proposed by the present invention in detail on the basis of the above embodiment, and the establishment of the adaptive template includes the following steps:
Step 11, defining the number and serial number of the epitopes of the adaptive template list; wherein, the smaller the epitope sequence number, the higher the priority level;
and step 12, initializing and filling the adaptive template list.
Preferably, the number of epitopes that can define the list of adaptive templates is 4, 8, 16 or 32; taking the number of the epitopes as 8 as an example, the serial numbers of the epitopes are sequentially arranged from 0 to 7, the smaller the serial number is, the higher the priority is, and each epitope records a group of reconstruction values of one MB. The MB size can be set, and in this embodiment, the size of MB is taken as an example, that is, the size of each MB is 8 × 2 pixels, that is, each MB has 8 × 2 reconstruction values.
Preferably, recording a set of reconstructed values for one MB per epitope may include: and filling the reconstruction values of the first 8 MB in the image into the list of the adaptive templates in sequence, wherein the filling sequence is the reverse filling according to the priority of the adaptive templates.
Storing 4 preset groups of reconstruction values at positions with epitope serial numbers of 4-7 in the self-adaptive template list; detecting the consistency of the reconstruction value of the adjacent MB on the current MB and the filled reconstruction value in the self-adaptive template list, and if the consistency is not available, filling the reconstruction value of the adjacent MB to the position with the epitope serial number of 0; if the consistency exists, the filled reconstruction value in the consistent adaptive template list is exchanged with the reconstruction value of the position with the epitope serial number of 0, and all the reconstruction values in the adaptive template list can be updated.
Detecting the consistency of the reconstruction value of the current MB left adjacent MB and the filled reconstruction value in the adaptive template list, and if the consistency is not available, filling the reconstruction value of the left adjacent MB to the position with the epitope serial number of 1; if the consistency exists, the filled reconstruction value in the consistent adaptive template list is exchanged with the reconstruction value of the position with the epitope serial number of 1, and all the reconstruction values in the adaptive template list can be updated.
Detecting the consistency of the reconstruction value of the upper left adjacent MB of the current MB and the filled reconstruction value in the adaptive template list, and if the consistency is not available, filling the reconstruction value of the upper left adjacent MB to the position with the epitope serial number of 2; if the table has consistency, the filled reconstruction value in the consistent adaptive template list is exchanged with the reconstruction value of the position with the epitope serial number of 2, and all the reconstruction values in the adaptive template list can be updated.
Detecting the consistency of the reconstruction value of the upper right adjacent MB of the current MB and the filled reconstruction value in the self-adaptive template list, and if the consistency is not available, filling the reconstruction value of the upper right adjacent MB to the position with the epitope serial number of 3; if the table has consistency, the filled reconstruction value in the consistent adaptive template list is exchanged with the reconstruction value of the position with the epitope serial number of 3, and all the reconstruction values in the adaptive template list can be updated.
The formula for detecting consistency is as follows:
where, Cur is the original pixel value of the current MB, CurRec is the reconstructed value of the current MB, ABS is the absolute value, Pred is the reconstructed value filled by any template in the template list, MBnum is the pixel number in the current MB, i is the adaptive template serial number corresponding to Pred in the template list, a1And a2Is a weight coefficient, Thr0Is a threshold value; wherein, when Thr is0Is greater than
When k is 1, when Thr0Is less than
When k is 0; when k is 1, it can be determined that consistency is present, otherwise it is determined that consistency is not present.
Preferably, the values of a1 and a2 can be preset fixed values;
further, a1+ a2 is 1; preferably, a1 can be selected as 0.5, a2 can be selected as 0.5, and a1 and a2 can also be flexibly adjusted in size.
EXAMPLE III
The present embodiment describes in detail another adaptive template prediction method proposed by the present invention on the basis of the above embodiments; referring to fig. 3, fig. 3 is a flowchart of another adaptive template prediction method according to an embodiment of the present invention. The prediction method comprises the following steps:
Specifically, adaptive texture prediction is performed on the pixel value of the current MB and the MB reconstructed values in the adaptive template list to obtain a reference pixel, please refer to fig. 4, where fig. 4 is a schematic diagram of an adjacent reference pixel of adaptive texture prediction according to an embodiment of the present invention; the method comprises the following steps:
a. if ABS (D-E) is minimal, i.e., 135 degree texture, then the reference pixel is pixel A;
b. if ABS (D-A) is minimal, i.e., vertical texture, then the reference pixel is pixel B;
c. if ABS (D-B) is minimal, i.e., 45 degree texture, then the reference pixel is pixel C;
d. if ABS (B-A) is minimal, i.e., horizontal texture, then the reference pixel is pixel D;
wherein ABS is an absolute value, A, B, C, E is a reconstruction value corresponding to a current pixel in any epitope of the template, i.e., a reconstruction value corresponding to the current pixel in any epitope of the template, and D is a reconstruction value of a pixel component adjacent to the left of the current pixel component, where pixel a is an upper-left neighboring reference pixel, pixel B is an upper neighboring reference pixel, pixel C is an upper-right neighboring reference pixel, pixel D is a left neighboring reference pixel, and pixel E is a left neighboring reference pixel of pixel a.
And 3, obtaining the prediction residual error of the current MB through point-to-point difference calculation.
According to the mode, the reference pixel is selected, the minimum value in the selected reference pixel is used as the final reference pixel, and the difference between the final reference pixel value and the pixel value of the current MB is obtained to obtain the prediction residual error adapting to the texture prediction mode.
And after the current MB finishes the self-adaptive prediction, continuously judging whether all the MBs in the image finish the prediction operation, if so, finishing the prediction, otherwise, skipping to the step 1, and continuously performing the prediction operation of the subsequent MB.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (6)
1. An adaptive template prediction method for bandwidth compression, comprising:
step 1, establishing a self-adaptive template list; the step 1 comprises the following steps: step 11, defining the number and serial number of the epitopes of the adaptive template list; wherein, the smaller the epitope sequence number, the higher the priority level; step 12, initializing and filling the adaptive template list;
step 2, updating the adaptive template list according to the MB reconstruction value of the adjacent reference direction of the current MB; the step 2 comprises the following steps: detecting whether the reconstruction value of the MB in the adjacent reference direction of the current MB is consistent with the reconstruction value filled in the adaptive template list or not, and if so, exchanging the consistent reconstruction value with the reconstruction value of the epitope serial number corresponding to the adaptive template list; otherwise, filling the reconstruction value of the MB in the adjacent reference direction into the epitope serial number corresponding to the adaptive template list;
step 3, performing adaptive prediction according to the adaptive template list to obtain a candidate reconstruction value of the current MB;
step 4, performing adaptive texture prediction according to the candidate reconstruction value to obtain a reference pixel of the current MB;
and 5, calculating the prediction residual of the current MB according to the reference pixel.
2. The method of claim 1, wherein the number of said epitopes is N, said epitopes are numbered 0 through N-1, and each of said epitopes is initialized with a set of reconstructed values for one MB.
3. The method of claim 1, wherein the neighboring reference direction comprises an upper neighboring reference direction, a left neighboring reference direction, an upper left neighboring reference direction, or an upper right neighboring reference direction.
4. The method according to claim 3, wherein the sequence number of the epitope corresponding to the upper adjacent reference direction is 0; the epitope serial number corresponding to the left adjacent reference direction is 1; the serial number of the epitope corresponding to the upper left adjacent reference direction is 2; and the serial number of the epitope corresponding to the upper right adjacent reference direction is 3.
5. The method of claim 4, wherein the step 3 comprises: and matching the pixel value of the current MB with the reconstruction value of each MB in the list of the adaptive templates, and selecting at least one group of reconstruction values as candidate reconstruction values.
6. The method of claim 5, wherein the step 4 comprises: and carrying out adaptive texture prediction on the pixel value of the current MB and the candidate reconstruction value to obtain a reference pixel of the current MB.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811261682.6A CN109561314B (en) | 2018-10-26 | 2018-10-26 | Self-adaptive template prediction method for bandwidth compression |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811261682.6A CN109561314B (en) | 2018-10-26 | 2018-10-26 | Self-adaptive template prediction method for bandwidth compression |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109561314A CN109561314A (en) | 2019-04-02 |
| CN109561314B true CN109561314B (en) | 2020-12-22 |
Family
ID=65865233
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811261682.6A Active CN109561314B (en) | 2018-10-26 | 2018-10-26 | Self-adaptive template prediction method for bandwidth compression |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109561314B (en) |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101415121B (en) * | 2007-10-15 | 2010-09-29 | 华为技术有限公司 | Self-adapting method and apparatus for forecasting frame |
| CN102045554A (en) * | 2009-10-22 | 2011-05-04 | 浙江大学 | Airspace prediction method and device of video and image |
| CN101841705A (en) * | 2010-03-12 | 2010-09-22 | 西安电子科技大学 | Video lossless compression method based on adaptive template |
| CN107181956B (en) * | 2011-10-07 | 2020-02-21 | 英迪股份有限公司 | Method for decoding video signal |
| CN102404566A (en) * | 2011-11-02 | 2012-04-04 | 无锡博视芯半导体科技有限公司 | Self-adapting scanning method used for entropy coding |
| CN103379318B (en) * | 2012-04-12 | 2018-01-19 | 中兴通讯股份有限公司 | A kind of coded video bit stream method and apparatus |
| US9591322B2 (en) * | 2013-12-30 | 2017-03-07 | New York University | Coding using a redundant dictionary, such as video coding using a self-adaptive redundant dictionary including spatial and/or temporal prediction candidate atoms |
| CN107925759B (en) * | 2015-06-05 | 2022-06-03 | 杜比实验室特许公司 | Method and apparatus for encoding and decoding intra prediction |
| CN105704496A (en) * | 2016-03-25 | 2016-06-22 | 符锌砂 | Adaptive template matching algorithm based on edge detection |
| CN108063947B (en) * | 2017-12-14 | 2021-07-13 | 西北工业大学 | Lossless reference frame compression method based on pixel texture |
-
2018
- 2018-10-26 CN CN201811261682.6A patent/CN109561314B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN109561314A (en) | 2019-04-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP4357543B2 (en) | Method and system for estimating pixel intra prediction mode | |
| TWI239207B (en) | Method and device for coding digital images using intra-mode block prediction | |
| US20100309977A1 (en) | Adaptive Intra Mode Selection | |
| CN101540911B (en) | Method and device for generating an image data stream, method and device for reconstructing a current image from an image data stream | |
| CN108353175A (en) | The method and apparatus of prediction processing vision signal caused by coefficient of utilization | |
| CN116647693A (en) | Encoding/decoding apparatus, storage medium, and data transmission apparatus | |
| CN109561314B (en) | Self-adaptive template prediction method for bandwidth compression | |
| US20120213449A1 (en) | Prediction of Pixels in Image Coding | |
| CN111107344A (en) | Video image coding method and device | |
| CN114143536B (en) | Video coding method of SHVC (scalable video coding) spatial scalable frame | |
| CN111200730A (en) | Multi-mode two-stage selection prediction method for complex texture in bandwidth compression | |
| CN114143537A (en) | All-zero block prediction method based on possibility size | |
| CN109413420B (en) | Dual-mode selection prediction method for complex texture in bandwidth compression | |
| CN116325727A (en) | Intra-frame prediction method, encoder, decoder and storage medium | |
| CN109302615B (en) | Self-adaptive template prediction method for video compression | |
| CN109510996B (en) | Post-selection prediction method in bandwidth compression | |
| CN111200731A (en) | Multi-mode two-stage selection prediction method for complex texture in bandwidth compression | |
| CN109510986B (en) | Self-adaptive texture gradual change prediction method in bandwidth compression | |
| CN109600608B (en) | Dual-mode selection prediction method for complex texture in bandwidth compression | |
| CN103856780A (en) | Video encoding method, decoding method, encoding device and decoding device | |
| CN109561308B (en) | Self-adaptive texture gradual change prediction method in bandwidth compression | |
| CN109510983B (en) | Multi-mode selection prediction method for complex texture in bandwidth compression | |
| CN109547795B (en) | Video coding method and device | |
| CN109660793B (en) | Prediction method for bandwidth compression | |
| CN111107350A (en) | Dual-mode selection prediction method for complex texture in bandwidth compression |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20201201 Address after: B07-01-21, 7th floor, block B, No. 705, Asia Pacific Road, Daqiao Town, Nanhu District, Jiaxing City, Zhejiang Province Applicant after: Jiaxing Aoheng import and Export Co.,Ltd. Address before: 710065 No. 86 Leading Times Square (Block B), No. 2, Building No. 1, Unit 22, Room 12202, No. 51, High-tech Road, Xi'an High-tech Zone, Shaanxi Province Applicant before: XI'AN CREATION KEJI Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP01 | Change in the name or title of a patent holder | ||
| CP01 | Change in the name or title of a patent holder |
Address after: B07-01-21, 7th floor, block B, No. 705, Asia Pacific Road, Daqiao Town, Nanhu District, Jiaxing City, Zhejiang Province Patentee after: Jiaxing aoteng Electronic Technology Co.,Ltd. Address before: B07-01-21, 7th floor, block B, No. 705, Asia Pacific Road, Daqiao Town, Nanhu District, Jiaxing City, Zhejiang Province Patentee before: Jiaxing Aoheng import and Export Co.,Ltd. |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20240122 Address after: 314300, Group 2, Bazi Village, Yucheng Town, Haiyan County, Jiaxing City, Zhejiang Province Patentee after: Haiyan Wantong Fasteners Co.,Ltd. Country or region after: China Address before: B07-01-21, 7th floor, block B, No. 705, Asia Pacific Road, Daqiao Town, Nanhu District, Jiaxing City, Zhejiang Province Patentee before: Jiaxing aoteng Electronic Technology Co.,Ltd. Country or region before: China |