Tile-Based Image Decoding With Dependent Slice Processing
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Solution Overview
Problem
There is a need to improve efficiency in image coding and decoding methods when both parallel tile processing and dependent slices are used, as existing methods face limitations in compression efficiency and parallel processing compatibility.
Innovation Solution
An image coding and decoding method that allows decoding of slices, where normal slices start from the beginning of a tile and dependent slices utilize information from another slice's header, ensuring efficient parallel processing without restarting CABAC at the beginning of each slice.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If dependent slices are used to improve compression efficiency, then compression efficiency is improved, but parallel processing capability deteriorates
Solution Approach 1:
The image is divided into multiple tiles, and each tile is independently decoded. Within each tile, slices are further segmented. This segmentation allows parallel processing at the tile level while maintaining dependent slice structures within tiles, thus resolving the contradiction between compression efficiency and parallel processing capability.
Solution Approach 2:
Different regions (tiles) of the image are processed with different qualities - the first tile contains normal slices with complete headers for independence, while subsequent tiles contain dependent slices for compression efficiency. This local differentiation allows both parallel processing and compression efficiency to coexist.
2Speed
If parallel tile processing is implemented to improve processing speed, then processing speed is improved, but slice dependency management becomes complex
Solution Approach 1:
By segmenting the image into independent tiles, each tile can be processed in parallel without affecting others. The first tile is processed independently with normal slices, while subsequent tiles use dependent slices that reference only within their own tile, simplifying dependency management despite parallel processing.
Solution Approach 2:
The slice header information is extracted and managed separately - the first tile's slices contain complete header information, while subsequent tiles extract only the necessary differences. This separation simplifies the management of slice dependencies during parallel processing.
3Adaptability or versatility
If normal slices start from position other than tile beginning to improve flexibility, then flexibility is improved, but decoding complexity increases
Solution Approach 1:
The image is segmented into tiles, with each tile containing complete slice structures. This segmentation allows flexible slice positioning within tiles while maintaining independent decoding of each tile, thus improving flexibility without significantly increasing overall decoding complexity.
Data Source
AI summary
An image decoding method for decoding a bitstream including a coded signal resulting from coding tiles and slices into which an image is partitioned, the method including decoding the coded signal, wherein each of the slices is either a normal slice having, in a header, information used for an other slice or a dependent slice which is decoded using information included in a slice header of another slice, and when the normal slice starts from a position other than a beginning of a first tile, a second tile coded next to the first tile does not start from the dependent slice.