Transform Coefficient Level Coding for Mixed-Value Residuals
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality images and videos, particularly in virtual reality and augmented reality, necessitates a more efficient compression technique to reduce transmission and storage costs, as existing methods struggle with the higher data volume and diverse characteristics of these media.
Innovation Solution
A method for enhancing video/image coding efficiency by improving residual coding efficiency, specifically through level coding for transform coefficients, which includes context-adaptive binary arithmetic coding and entropy encoding techniques to handle low and high level values effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional video coding methods are used for high-resolution images and videos, then image/video quality is maintained, but transmission and storage costs increase due to larger data volume
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the transform block size based on the characteristics of the image block being encoded. When encoding high-resolution images and videos, the system selectively uses different transform block sizes (e.g., 4x4, 8x8, 16x16) depending on the complexity and frequency content of the block. This adaptive parameter adjustment optimizes the balance between maintaining image quality and reducing the amount of data that needs to be transmitted and stored, directly addressing the contradiction between quality preservation and data volume reduction.
2Productivity
If transform block size is increased to reduce coding complexity, then encoding speed improves, but coding accuracy for transform coefficients deteriorates
Solution Approach 1:
The patent implements segmentation by dividing the transform process into multiple stages with different block sizes. Instead of applying a single large transform block to the entire image, the system segments the image into smaller blocks and applies appropriate transform sizes to each segment based on its characteristics. This segmentation approach allows the encoder to maintain high processing speed by handling smaller blocks individually while achieving high coding accuracy through selective use of larger transform blocks in suitable regions, thus resolving the contradiction between encoding speed and coding accuracy.
3Device complexity
If fixed transform block size is used, then encoding process is simplified, but adaptability to different image characteristics is reduced
Solution Approach 1:
The patent applies dynamics by making the transform block size adaptive rather than fixed. The system dynamically selects the appropriate transform block size based on real-time analysis of image characteristics such as edge detection, gradient magnitude, and frequency content. This dynamic adaptation allows the encoding process to automatically adjust to different image regions and characteristics without requiring complex manual configuration, thereby maintaining relative simplicity while achieving high adaptability to various image types and content.
Data Source
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AI summary
A video decoding method performed by a decoding apparatus according to the present document may comprise the steps of: obtaining, from a bitstream, information indicating a level value of a transform coefficient in a current block; selecting one Rice parameter look-up table for the information indicating the level value of the transform coefficient, from among a plurality of Rice parameter look-up tables; deriving a Rice parameter for the information indicating the level value of the transform coefficient on the basis of the selected Rice parameter look-up table; deriving a bin string for the information indicating the level value of the transform coefficient on the basis of the Rice parameter; and deriving the level value of the transform coefficient on the basis of the bin string.