Image Windowing Signaling for Reduced Encoding Overhead
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Solution Overview
Problem
Existing digital media encoding and decoding technologies face inefficiencies in compressing and decompressing large images due to significant overhead from index table representation and complexity in handling large image dimensions and alpha channel information, which degrades compression efficiency and increases computational complexity.
Innovation Solution
The implementation of techniques such as INDEXTABLE_PRESENT_FLAG for flexible index table signaling, SHORT_HEADER_FLAG for reduced overhead in signaling image and tile dimensions, and independent processing of alpha channel information to reduce complexity and enhance coding performance, along with block transform-based coding for efficient compression and decompression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If index table representation is used for tiled images, then image decoding capability is improved, but overhead and computational complexity increase significantly
Solution Approach 1:
The patent extracts and processes only the necessary index table information rather than handling the complete index table. By selectively decoding and using only relevant index entries corresponding to the window region, the system maintains full decoding capability while significantly reducing overhead and computational complexity.
Solution Approach 2:
The patent segments the image decoding process into distinct regions: the window region of interest and the rest of the image. By applying different processing strategies to different segments (full index table processing for the window region, simplified processing for other regions), the system achieves versatile decoding capability with reduced overall complexity.
2Measurement precision
If large image dimensions are handled with complete index table processing, then decoding accuracy is improved, but compression efficiency degrades
Solution Approach 1:
The patent applies different processing qualities to different regions: high-quality complete index table processing is applied only to the window region where high decoding accuracy is needed, while simplified processing is applied to other regions. This local differentiation maintains decoding accuracy where required while improving overall compression efficiency.
Solution Approach 2:
Instead of processing the complete index table for the entire large image, the patent applies partial processing only to the extent necessary for the window region. This partial action approach maintains sufficient decoding accuracy for the region of interest while significantly reducing the computational energy consumed, thereby improving compression efficiency.
3Reliability
If alpha channel information is processed jointly with image data, then coding performance is improved, but computational complexity increases
Solution Approach 1:
The patent segments the processing into separate stages: first processing the image data to identify the window region, then processing alpha channel information specifically for that identified region. This segmentation maintains joint processing benefits for coding performance while reducing computational complexity by avoiding redundant alpha channel processing outside the window region.
Data Source
AI summary
Techniques and tools for signaling and using image tiling information (such as syntax elements relating index tables and header size), signaling and using windowing information (such as techniques for using windowing parameters when rotating, cropping or flipping images), and signaling and using alpha channel information are described.