Image Decoding SAO Signaling Picture Slice Level
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to larger information sizes, resulting in increased transmission and storage costs when using conventional wired/wireless broadband lines or storage media.
Innovation Solution
An image decoding method that includes obtaining indication information with a flag indicating whether the Sample Adaptive Offset (SAO) procedure is applied at a picture level or a slice level, parsing SAO information from the picture or slice header, generating prediction samples, and performing the SAO procedure on reconstructed samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image data is transmitted using conventional wired/wireless broadband lines, then image quality is improved, but transmission cost increases
Solution Approach 1:
The patent extracts and removes redundant information from image data through compression techniques. By identifying and eliminating unnecessary data elements while preserving essential visual information, the system achieves high-quality image transmission with reduced bit size, directly addressing the contradiction between image quality and transmission cost
Solution Approach 2:
Instead of transmitting all image data and then selecting quality portions, the patent inverts the approach by first compressing to essential information and then enhancing only the most critical visual elements. This inversion allows achieving high perceived quality with minimal transmission resources
2Measurement precision
If high-resolution and high-quality image data is stored using conventional storage media, then image quality is improved, but storage cost increases
Solution Approach 1:
The patent extracts and removes redundant information from image data through compression techniques. By identifying and eliminating unnecessary data elements while preserving essential visual information, the system achieves high-quality image storage with reduced bit size, directly addressing the contradiction between image quality and storage cost
3Measurement precision
If SAO procedure information is signaled at every block level, then decoding precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the image data into blocks and applies SAO procedure selectively rather than uniformly. By dividing the processing into hierarchical levels (picture level, slice level, block level) and applying appropriate precision at each level, the system achieves high decoding precision for critical regions while reducing overall computational complexity
Solution Approach 2:
The patent applies different levels of SAO processing precision to different regions of the image based on their importance. Critical regions receive full precision processing while less important regions use simplified processing, optimizing the balance between decoding precision and device complexity
4Productivity
If conventional image compression techniques are used, then transmission efficiency is improved, but image quality deteriorates
Solution Approach 1:
The patent changes the parameters of compression by introducing Sample Adaptive Offset (SAO) procedures that adjust compression behavior based on local image characteristics. By dynamically modifying compression parameters according to image content, the system maintains high transmission efficiency while preserving or enhancing image quality in critical regions
Solution Approach 2:
The patent applies preliminary SAO processing to reconstructed samples before final output. This preliminary action of adding offset corrections after reconstruction compensates for compression artifacts, improving image quality without significantly impacting transmission efficiency
Data Source
AI summary
An image decoding method performed by a decoding device according to the present disclosure comprises the steps of: obtaining prediction-related information and indication information comprising a first flag which indicates whether or not a sample adaptive offset (SAO) process to be applied to a current block is applied at a picture level or a slice level; parsing information related to the SAO process from a picture header or a slice header on the basis of the first flag; generating prediction samples for the current block on the basis of the prediction-related information; generating reconstructed samples for the current block on the basis of the prediction samples; and performing the SAO process for the reconstructed samples on the basis of the information related to the SAO process.