Video Encoding Using Region-Based Resolution Scaling
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Solution Overview
Problem
Existing video encoding and decoding technologies face challenges in efficiently managing bandwidth while maintaining high video quality, particularly in transmitting video signals with varying pixel resolutions over limited bandwidth channels.
Innovation Solution
The method involves subdividing video frames into regions with predetermined inter-block data consistency, determining predictors for each region, and encoding these regions by scaling to a specific size, allowing for efficient encoding and decoding of video signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video frames are encoded at high pixel resolution to maintain video quality, then video quality is improved, but bandwidth consumption increases
Solution Approach 1:
The video frame is divided into multiple regions with different resolutions. The encoder identifies important regions (e.g., containing motion or detail) and encodes them at higher resolution, while less important regions are encoded at lower resolution. This segmentation allows the system to maintain overall video quality while reducing total bandwidth consumption by allocating bits selectively rather than uniformly across the entire frame.
2Loss of energy
If uniform downscaling is applied to all frames before encoding to reduce bandwidth, then bandwidth consumption is reduced, but video quality deteriorates
Solution Approach 1:
Instead of applying uniform downscaling to the entire frame, the encoder applies different scaling factors to different regions based on their importance. Regions containing significant motion, detail, or visual interest are scaled less (maintaining higher quality), while regions with less visual importance are scaled more (reducing bandwidth). This local quality approach ensures that bandwidth is reduced overall while critical video quality is preserved.
3Measurement precision
If the entire frame is processed at high resolution to maintain detail, then video quality is improved, but encoding complexity and computational resources increase
Solution Approach 1:
The frame is segmented into regions of different importance, and encoding is performed at different resolutions for each region. This segmentation reduces the total number of high-resolution pixels that need to be processed, thereby reducing encoding complexity and computational resource requirements while maintaining video quality in the most important regions.
4Loss of energy
If resolution scaling is applied selectively to different regions, then bandwidth efficiency is improved, but device complexity increases
Solution Approach 1:
The encoder performs preliminary analysis of the frame to identify important regions before the actual encoding process. This preliminary action includes detecting motion, identifying regions of interest, and determining which areas require high-resolution encoding. By performing this analysis beforehand, the system can efficiently allocate resources during encoding without excessive complexity, as the difficult decisions about resolution allocation are made in advance.
Data Source
AI summary
An apparatus and method for encoding and decoding a video signal having a plurality of frames is disclosed. The encoding method subdivides at least one frame of the plurality of frames into a plurality of regions where each region is composed of different numbers of blocks based on their data consistency. Each region is encoded using residual having a common size. In this way, different parts of the image may be encoded at different resolutions.