Video Coding Saliency Map Bandwidth Optimization
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Solution Overview
Problem
Current video compression techniques fail to effectively manage bandwidth requirements for growing video content, as they do not adequately differentiate between the importance of pixels in a frame, leading to inefficient data transmission and potential reduction in image quality for less noticeable areas.
Innovation Solution
The proposed technique uses a saliency map to determine the relative importance of pixels in a video frame, applying a variance weighted chromatic activity map and tone map functions to selectively attenuate inter-frame differences, leveraging color science principles and block-based progressive video coding, and employing motion compensation and entropy coding to reduce bit rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform compression is applied to all pixels in a video frame, then the compression ratio is simplified and processing is easier, but the image quality deteriorates in important regions and bandwidth requirements increase
Solution Approach 1:
The patent applies different compression strategies to different regions of the video frame based on a saliency map. Important regions (high saliency) are encoded with higher quality and less compression, while less important regions (low saliency) are encoded with lower quality and higher compression. This local differentiation resolves the contradiction by maintaining image quality where needed while achieving overall compression efficiency.
2Quantity of substance
If higher compression is applied to less important pixels, then bandwidth usage is optimized, but image quality deteriorates in those regions
Solution Approach 1:
The patent changes the compression parameters (quantization step size, bitrate allocation) based on the saliency values of different regions. For low-saliency regions, more aggressive compression parameters are applied, accepting quality degradation that is imperceptible to human observers. This resolves the contradiction by making quality deterioration acceptable in regions where it does not matter visually.
3Productivity
If a saliency map is generated and used for selective encoding, then compression gain is improved and bandwidth is optimized, but device complexity increases
Solution Approach 1:
The patent generates the saliency map as a preliminary step before the actual video encoding process. This pre-computed saliency information guides subsequent encoding decisions, allowing the encoder to allocate bits efficiently without adding complexity to the core encoding algorithm. The saliency map serves as a lookup table that simplifies real-time encoding decisions.
Data Source
AI summary
A video coder includes a processing resource and a non-transitory storage device containing instructions executable by the processing resource to compute a weighted Δ frame based on a saliency map and a Δ frame. The saliency map is to indicate the relative importance of each pixel in a current frame based on its perceptual significance. The Δ frame is to include differences between corresponding pixels in a current frame and a motion predicted frame.