Depth Map Block Encoding Using DMM Mode Detection
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Solution Overview
Problem
Current 3D encoding and decoding technologies face high complexity and low efficiency due to the need to detect multiple modes during the encoding and decoding of depth map blocks, particularly with the use of recursive quadtree encoding and simplified depth coding in conjunction with depth modeling modes.
Innovation Solution
The method involves detecting only two modes, DMM1 and DMM4, by determining the mode with the smallest rate-distortion result and applying it to recursive quadtree or simplified depth coding for encoding and decoding, and writing the used mode to a bitstream to guide the decoder.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple DMM modes (DMM1, DMM4) are detected during encoding and decoding of depth map blocks, then encoding/decoding accuracy is improved, but encoding/decoding complexity increases
Solution Approach 1:
The patent extracts and removes the mode detection step from the encoding/decoding process. By directly applying DMM to depth map blocks without detecting multiple DMM modes first, the solution eliminates the complexity associated with mode detection while maintaining encoding accuracy through direct application of the depth modeling technique.
Solution Approach 2:
The patent segments the depth map into multiple depth map blocks and applies DMM to each block independently. This segmentation approach allows the system to achieve accurate encoding/decoding by processing smaller units separately, avoiding the need for complex global mode detection while maintaining precision at the block level.
2Manufacturing precision
If multiple DMM modes are detected during encoding and decoding, then encoding/decoding quality is improved, but processing time increases
Solution Approach 1:
The patent removes the time-consuming mode detection step from the encoding/decoding workflow. By directly applying DMM to depth map blocks without performing multiple mode detections, the solution significantly reduces processing time while preserving encoding quality through the direct application of the depth modeling approach.
Solution Approach 2:
The patent performs preliminary segmentation of the depth map into blocks before encoding/decoding. This preliminary action organizes the data structure in advance, allowing direct application of DMM without subsequent mode detection steps, thereby reducing processing time while maintaining quality through pre-organized block processing.
3Manufacturing precision
If four DMM modes are detected during encoding/decoding of depth map blocks, then encoding/decoding performance is improved, but encoding/decoding efficiency decreases
Solution Approach 1:
The patent extracts and eliminates the multi-mode detection process from the encoding/decoding pipeline. By directly applying DMM to depth map blocks without detecting four different DMM modes, the solution removes the bottleneck that reduced efficiency, thereby improving productivity while maintaining performance through direct DMM application.
Solution Approach 2:
The patent segments the depth map processing into independent blocks that can be processed in parallel. This segmentation enables efficient processing by allowing multiple blocks to be handled simultaneously without the overhead of detecting four DMM modes sequentially, thus improving encoding/decoding efficiency while preserving performance.
Data Source
AI summary
The present invention discloses an intra-frame depth map block decoding method, including: acquiring, from a bitstream, a depth modeling mode (DMM) used for a depth map block, wherein the DMM is applied to a recursive quadtree (RQT) coding or simplified depth coding (SDC); obtaining a block predicted value of a depth map subblock obtained through segmentation in the DMM according to the DMM; acquiring, from the bitstream, a block offset value of the depth map subblock, and residual information of each pixel in the depth map subblock; and obtaining a reconstruction value of each pixel in the depth map subblock according to the block predicted value, the block offset value and the residual information of each pixel in the depth map subblock.