Frame Buffer Compressor Using Dynamic QP and Entropy Tables
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Image processing devices face limitations in processing capability due to increased bandwidth demands for high-definition video images, leading to decreased speed during video recording and playback.
Innovation Solution
An image processing device with a frame buffer compressor that determines a combination of a quantization parameter (QP) table and an entropy table to optimize image data compression, including a logic circuit for controlling compression based on these tables, thereby reducing bandwidth and enhancing processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing devices handle high-definition video images with increased bandwidth, then image quality and resolution are improved, but processing capability reaches its limit and speed decreases
Solution Approach 1:
The patent changes the parameters of quantization tables and entropy encoding tables dynamically based on image characteristics. By adjusting quantization parameters (QP values) and entropy table configurations according to the complexity and content of different image regions, the system achieves optimal compression ratios while maintaining processing speed within device capabilities.
2Quantity of substance
If bandwidth is increased to support high-definition video, then data access capacity is improved, but processing capability becomes a bottleneck
Solution Approach 1:
The patent performs preliminary compression actions by determining and applying appropriate quantization and entropy tables before full data processing. The system pre-calculates optimal compression parameters based on image statistics and applies them in advance, reducing the processing load on the main processing unit and preventing capability bottlenecks.
3Productivity
If compression is optimized using QP table and entropy table combinations, then compression efficiency is improved, but processing complexity increases
Solution Approach 1:
The patent implements dynamic selection of QP table and entropy table combinations based on real-time image characteristics. The system continuously adapts the compression parameters according to the statistical properties of the input image data, achieving high compression efficiency without requiring complex fixed-structure processing circuits.
Solution Approach 2:
The compression system performs self-optimization by automatically selecting appropriate QP and entropy table combinations based on image statistics without requiring external intervention. The logic circuit autonomously determines the best compression parameters by analyzing the input data characteristics and adjusting the tables accordingly.
Data Source
AI summary
An image processing device includes a multimedia intellectual (IP) block which processes image data; a memory; and a frame buffer compressor (FBC) which compresses the image data to generate compressed data and stores the compressed data in the memory. The frame buffer compressor includes a logic circuit which determines a combination of a quantization parameter (QP) table and an entropy table and controls compression of the image data based on the determined combination of the QP table and the entropy table.