Block-Based Depth Map Coding Using Bitplane XOR Operations
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Solution Overview
Problem
Existing video coding methods are inefficient in encoding and decoding depth maps due to their unique characteristics, which affect the quality of reconstructed images with different view-points in 3D video coding, particularly because they were developed for image information compression rather than depth information.
Innovation Solution
A method and apparatus for efficiently encoding and decoding depth maps by performing bitplane decoding in units of blocks, adaptively applying XOR operations, and combining bitplane blocks, along with decoding coding mode information and using Discrete Cosine Transform (DCT)-based decoding, to improve coding efficiency and picture quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If existing image information coding methods are used to encode depth maps, then the coding process is simple and compatible with existing standards, but the coding efficiency is poor and picture quality is degraded
Solution Approach 1:
The depth map is divided into multiple blocks, and each block is processed independently through bitplane segmentation. The bitplanes are further divided into sub-blocks that are encoded separately, allowing the coding method to adapt to the specific characteristics of depth map data while maintaining compatibility with existing coding frameworks.
Solution Approach 2:
Different coding techniques are applied to different blocks and bitplanes based on their specific characteristics. The method adaptively selects coding modes for each block, applying more complex processing where needed and simpler processing where appropriate, thereby optimizing coding efficiency without uniformly complicating the entire process.
2Ease of manufacture
If existing image information coding methods are used to encode depth maps, then implementation is straightforward, but picture quality of reconstructed images deteriorates
Solution Approach 1:
By segmenting the depth map into blocks and bitplanes, the method can apply targeted processing to preserve important depth information that directly affects picture quality, while keeping the overall implementation structure relatively simple and manageable.
Solution Approach 2:
The method transforms the coding process from operating on entire images to operating on bitplane blocks, adding a new dimension of processing granularity. This allows fine-tuned control over the coding process to preserve picture quality without fundamentally redesigning the entire coding framework.
3Adaptability or versatility
If more cameras with different view-points are used to provide multi-view images, then the variety of view-points is increased, but the amount of image data to be processed increases
Solution Approach 1:
The method extracts and processes only the essential depth information from the multi-view images through block-based bitplane coding. By focusing on encoding only the necessary depth map data rather than all image data, the system reduces the quantity of data to be processed while maintaining the ability to provide diverse view-points.
Solution Approach 2:
The patent introduces a new dimension of data representation through bitplane decomposition and block-based processing. This allows the system to represent depth information more efficiently, reducing the overall data volume required while maintaining the versatility to provide multiple view-points.
4Adaptability or versatility
If 3D video coding codes depth maps in addition to image information, then virtual view-points can be created, but the encoding and decoding processes become more complex
Solution Approach 1:
The depth map coding process is segmented into independent blocks and bitplanes, each processed separately. This segmentation allows the complex task of depth map encoding to be broken down into manageable units, reducing the perceived complexity while enabling virtual view-point creation.
Solution Approach 2:
Different coding modes are applied locally to different blocks based on their specific characteristics. This localized approach allows the system to handle the complexity of depth map encoding in a manageable, adaptive manner, creating virtual view-points without uniformly increasing system complexity.
Data Source
AI summary
Provided are a block-based depth map coding method and apparatus and a 3D video coding method using the same. The depth map coding method decodes a received bitstream in units of blocks of a predetermined size using a bitplane decoding method to reconstruct a depth map. For example, the depth map coding method may decode the bitstream in units of blocks using the bitplane decoding method or an existing Discrete Cosine Transform (DCT)-based decoding method adaptively according to decoded coding mode information. The bitplane decoding method may include adaptively performing XOR operation in units of bitplane blocks. For example, a determination on whether or not to perform XOR operation may be done in units of bitplane blocks according to the decoded value of XOR operation information contained in the bitstream.