Region-Based Image Filtering for Better Compression Efficiency
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Solution Overview
Problem
Conventional image processing methods apply filtering to entire image frames without considering regional characteristics, leading to reduced image quality and inefficient resource usage, as well as unsatisfactory compression results.
Innovation Solution
An encoding apparatus and method that select an optimum region division mode for an image frame, transmit this mode to a decoding apparatus, and apply independent filtering to each region using an optimum filtering method and coefficient, based on cost functions, to improve image processing results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If filtering is applied to the entire image frame without considering regional characteristics, then the processing is simple and fast, but the image quality is reduced and resources are used inefficiently
Solution Approach 1:
The image frame is divided into multiple regions with different characteristics (e.g., smooth regions, edge regions, texture regions). Each region is processed independently with appropriate filtering strategies, allowing quality optimization for each region while managing overall processing complexity through systematic division.
Solution Approach 2:
Different filtering methods and parameters are applied to different regions based on their local characteristics. For example, stronger filtering is applied to smooth regions while preserving details in edge and texture regions, achieving local optimization of image quality without uniformly processing the entire frame.
2Productivity
If filtering is applied to the entire image frame, then uniform processing is achieved, but excessive resources are used and compression effect is unsatisfactory
Solution Approach 1:
The image frame is segmented into regions with similar characteristics, allowing the system to process only relevant regions with appropriate filtering strength. This reduces unnecessary resource consumption in regions where filtering is less effective or unnecessary, thereby improving compression efficiency.
Solution Approach 2:
Instead of applying filtering uniformly across the entire image frame, the system applies filtering selectively to specific regions where it is most beneficial. This partial action approach optimizes resource usage by avoiding excessive filtering in regions where it would not improve compression效果.
3Manufacturing precision
If region division mode is selected and independent filtering is applied to each region, then image quality is enhanced, but processing complexity increases
Solution Approach 1:
The image frame is divided into multiple regions with distinct characteristics, and filtering is applied independently to each region. This segmentation allows quality optimization for each region while managing processing complexity through systematic regional division and standardized filtering procedures for each region type.
Solution Approach 2:
Different filtering methods and parameters are applied to different regions based on their local characteristics such as smoothness, edge density, and texture patterns. This local optimization enhances image processing quality by adapting to regional variations while maintaining manageable complexity through region-based categorization.
Data Source
AI summary
Region-based encoding apparatus and decoding apparatus. The encoding apparatus selects an optimum region division mode from region division modes with respect to regions divided from an image frame, and transmits, to the decoding apparatus, an optimum image filtering method and an optimum filter coefficient of regions divided, according to the optimum region division mode.