Image Display Driving Region-Based Filtering for Noise Reduction
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Solution Overview
Problem
Conventional image display technologies degrade image quality by uniformly filtering image data, leading to increased noise in smooth regions and reduced clarity, as they enhance edge or detail regions at the expense of smooth regions.
Innovation Solution
An apparatus and method that detect smooth, edge, and detail regions in image data and adjust gray scale or chrominance differently in each region, using characteristic-based region detection units and a data processor to generate converted image data for improved image clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If uniform filtering is applied to enhance edge and detail regions, then clarity in edge/detail regions is improved, but noise increases in smooth regions
Solution Approach 1:
The patent applies different filtering strengths to different image regions by classifying pixels into smooth, edge, and detail regions. Smooth regions receive strong filtering to reduce noise, while edge and detail regions receive weaker filtering to preserve clarity. This is achieved through region classification units that analyze local image characteristics and adjust filtering parameters accordingly, resolving the contradiction between noise reduction and clarity preservation.
Solution Approach 2:
The image is segmented into three distinct regions (smooth, edge, and detail regions) based on local characteristics. Each region is then processed with appropriate filtering strength. This segmentation allows the system to simultaneously reduce noise in smooth regions while maintaining clarity in edge and detail regions, directly addressing the technical contradiction.
2Measurement precision
If strong filtering is applied to improve image clarity, then edge and detail regions are enhanced, but image quality in smooth regions is degraded
Solution Approach 1:
The system adjusts filtering strength locally based on region classification. Smooth regions are identified and subjected to stronger filtering appropriate for noise reduction, while edge and detail regions are identified and given weaker filtering to preserve their clarity. This local quality adjustment resolves the contradiction between overall clarity improvement and smooth region quality preservation.
Solution Approach 2:
The filtering parameter (filtering strength) is dynamically changed based on the classified region type. The system modifies the filtering parameter from strong (for smooth regions) to weak (for edge and detail regions), allowing optimal processing for each region type and resolving the quality degradation issue in smooth regions.
3Device complexity
If uniform filtering is applied across the entire image, then the processing is simple, but the image quality is compromised due to noise in smooth regions
Solution Approach 1:
The image is segmented into different region types through classification units that analyze local characteristics. This segmentation enables differentiated filtering processing that improves image quality by reducing noise in smooth regions while preserving edge and detail regions. Although the processing becomes more complex than uniform filtering, the segmentation approach is computationally efficient and delivers superior image quality results.
Data Source
AI summary
An apparatus and method for driving an image display apparatus are disclosed. The apparatus includes a display panel having a plurality of pixels, for displaying an image, a panel driver for driving the pixels of the display panel, an image data converter for detecting a smooth region, an edge region, and a detail region from externally input image data in units of at least one frame and generating converted image data by changing a gray scale or chrominance of the image data at different rates in the smooth region, the edge region and the detail region, and a timing controller for arranging the converted image data suitably for driving of the display panel, providing the arranged image data to the panel driver, and controlling the panel driver by generating a panel control signal.