Video Encoder Text Quality Preservation via Quantization
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Solution Overview
Problem
Video encoding technologies often degrade the perceptual quality of text in image frames due to inadequate quantization methods, particularly when compressing macro-blocks with high activity measures, leading to poor text quality in decoded images.
Innovation Solution
A video encoder determines whether a macro-block contains text and adjusts the quantization parameter accordingly, using a smaller value to ensure better preservation of text quality during the encoding process, thereby differentiating the treatment of text and non-text macro-blocks in terms of bit representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If video encoding uses standard quantization methods to compress image frames, then compression efficiency is improved, but text quality in decoded images deteriorates
Solution Approach 1:
The patent applies different quantization parameters to different regions of the image frame based on content type. Text regions are identified and assigned smaller quantization parameters to preserve quality, while non-text regions use larger parameters for better compression. This local differentiation resolves the contradiction by optimizing both compression efficiency and text quality in their respective regions.
Solution Approach 2:
The patent dynamically changes the quantization parameter based on the detected content type. When text is detected in a macro-block, the quantization parameter is reduced to preserve text quality. This parameter adaptation allows the system to maintain high text quality while still achieving good overall compression efficiency through selective application.
2Manufacturing precision
If video encoding uses smaller quantization parameters to preserve text quality, then text quality is improved, but bit-rate increases
Solution Approach 1:
The patent applies smaller quantization parameters only to text regions rather than the entire image frame. This localized approach preserves text quality while limiting the increase in overall bit-rate to only the necessary portions, thereby resolving the contradiction between text quality and bit-rate efficiency.
Solution Approach 2:
The patent uses a moderate reduction in quantization parameter for text regions rather than extreme compression or extreme quality preservation. This partial action approach achieves acceptable text quality while controlling the bit-rate increase, balancing both requirements effectively.
3Device complexity
If video encoding treats all macro-blocks uniformly, then device complexity is reduced, but text quality deteriorates due to inadequate differentiation
Solution Approach 1:
The patent introduces content-based differentiation by identifying text regions and applying specific quantization parameters to them. This local quality approach improves text quality while maintaining relatively simple implementation through straightforward region detection and parameter assignment, resolving the contradiction between complexity and quality.
Solution Approach 2:
The patent performs text region detection and quantization parameter assignment during the encoding process before actual compression. This preliminary action allows the system to prepare differentiated parameters for text regions, ensuring quality preservation without adding significant complexity to the core compression algorithm.
Data Source
AI summary
A video encoder receives a macro-block of an image frame, and determines whether the macro-block contains text. The video encoder computes a quantization parameter for quantizing the macro-block, with the quantization parameter computed to be smaller if the macro-block is determined to contain text. The video encoder encodes the macro-block using the quantization parameter. Text quality in the encoded macro-block is preserved.