Image Decoding Using Lossless Residual Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for high-resolution and high-quality images and videos, such as UHD and immersive media, necessitates a high-efficiency image and video compression technology to effectively compress and transmit or store these files, as existing methods incur high transmission and storage costs due to increased data volume.
Innovation Solution
An image decoding method and apparatus that improves coding efficiency by determining whether lossless coding is used, generating residual samples, and encoding image information, including residual information and lossless coding usage, to enhance overall image/video compression efficiency and reduce complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image and video data are transmitted or stored using existing methods, then image quality and resolution are improved, but transmission costs and storage costs are increased
Solution Approach 1:
The patent extracts and separately encodes residual information from the image data using lossless coding techniques. By isolating the residual component (the difference between original and predicted pixel values) and applying dedicated lossless coding to it, the method removes inefficiencies from the overall encoding process while preserving image quality.
Solution Approach 2:
The patent applies different coding strategies to different parts of the image data. Specifically, it applies lossless coding to the residual information while using other coding methods for the main image data. This localized application of lossless coding optimizes compression for the most critical part of the data without unnecessarily increasing complexity elsewhere.
2Productivity
If lossless coding is applied to residual information, then residual coding efficiency is improved, but coding complexity is increased
Solution Approach 1:
The patent applies lossless coding selectively only to the residual information portion of the image data, rather than to the entire image. This localized approach improves residual coding efficiency while limiting the increase in overall coding complexity to only the necessary components.
Solution Approach 2:
The patent segments the image encoding process into distinct components: main image data encoding and residual information encoding. By separating these components and applying appropriate coding methods to each, the system achieves improved residual coding efficiency while managing overall complexity through modular processing.
Data Source
AI summary
According to a disclosure of the present document, coding efficiency and complexity of residual coding may be improved on the basis of a determination regarding whether or not lossless coding is used.