Video Encoding Macroblock Classification for Text Compression
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Solution Overview
Problem
Current video encoding technologies are inefficient in compressing discontinuous tone content like text, particularly in scenarios with a large amount of text, such as desktop office environments, due to poor classification methods and inefficient compression techniques.
Innovation Solution
A video encoding method that performs macroblock division on screen change areas, classifies macroblocks as text or image based on pixel data, determines the appropriate compression type for text macroblocks based on color data, and applies corresponding compression quality to improve compression efficiency and applicability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional video encoding technologies are used to compress screen content, then general video compression is achieved, but compression efficiency for text content is poor
Solution Approach 1:
The patent divides the screen content into multiple macroblocks and further segments them into text macroblocks and image macroblocks based on pixel data characteristics. This segmentation allows different compression strategies to be applied to different content types, improving overall compression efficiency while preserving text quality.
Solution Approach 2:
The patent applies different compression types (first compression type for text, second compression type for images) to different macroblocks based on their content characteristics. This local quality approach ensures that text macroblocks receive appropriate compression treatment to maintain definition quality, while image macroblocks can use more aggressive compression.
2Manufacturing precision
If high compression quality is applied to maintain text definition, then text quality is preserved, but bandwidth requirements increase
Solution Approach 1:
The patent changes the compression parameters dynamically based on macroblock type. Text macroblocks use a first compression type with parameters optimized for preserving definition quality, while image macroblocks use a second compression type with parameters optimized for compression ratio. This parameter adaptation reduces overall bandwidth requirements while maintaining text quality.
3Productivity
If uniform compression is applied to all macroblocks, then processing is simple, but compression efficiency for mixed content is poor
Solution Approach 1:
The patent segments macroblocks into text and image categories based on pixel data analysis, then applies different compression types to each segment. This segmentation enables improved compression efficiency for mixed content while keeping the classification logic relatively simple and systematic.
Solution Approach 2:
The patent creates a universal encoding framework that can handle both text and image macroblocks using a single classification and processing system. The system universally applies the same macroblock division and classification approach to all content, then adapts compression parameters based on content type, achieving multi-functionality without excessive complexity.
Data Source
AI summary
Provided are video encoding and decoding methods and apparatuses, a video encoding and decoding system, and a storage medium. The video encoding method includes: performing macroblock division on pixel data of a screen change area, classifying, according to pixel data in a divided macroblock, the divided macroblock as a text macroblock or an image macroblock; determining a compression type of the text macroblock according to color data in the text macroblock; and performing encoding and compression, according to the compression type of the text macroblock, on the text macroblock with a corresponding compression quality.