False Contour Detection Circuit for Image Detail Preservation
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Solution Overview
Problem
Conventional image processing methods fail to accurately distinguish between false contours and small details like weak edges and fine textures, leading to loss of image details during false contour detection.
Innovation Solution
An image processing apparatus and method that includes a false contour detection circuit with multiple detection modules and a determination module to generate feature coefficients, which are used to determine a false contour coefficient for precise detection and reduction, preventing loss of image details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only gradient-based method is adopted to detect false contours, then false contour detection is simplified, but small details like weak edges and fine textures are mistakenly detected as false contours leading to loss of image details
Solution Approach 1:
The patent divides the false contour detection process into multiple independent detection modules, each responsible for detecting specific features (gradient, texture, edge strength). This segmentation allows the system to analyze different characteristics separately and combine them for accurate false contour identification, preventing misclassification of important image details.
Solution Approach 2:
The patent changes the detection parameters by introducing multiple feature coefficients (gradient coefficient, texture coefficient, edge strength coefficient) instead of relying solely on gradient-based detection. This multi-parameter approach enables the system to distinguish between actual false contours and legitimate image details like weak edges and fine textures by evaluating multiple characteristics simultaneously.
2Measurement precision
If multiple detection modules are used to detect different features, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple detection modules (gradient detection, texture detection, edge strength detection) into a unified false contour detection circuit. These modules work together and their output feature coefficients are combined by a determination module to generate the final false contour coefficient, achieving high detection accuracy while maintaining circuit integration.
Solution Approach 2:
The determination module serves multiple functions: it receives feature coefficients from different detection modules, processes them according to a determination formula, and generates the false contour coefficient. This multi-functional design reduces overall device complexity by using a single module to handle multiple detection tasks.
Data Source
AI summary
An image processing apparatus and method thereof are provided. The image processing apparatus includes a false contour detection circuit and a false contour reduction circuit. The false contour detection circuit includes detection modules and a determination module. The detection modules respectively detect different features of the same image input signal and correspondingly output feature coefficients. The determination module is coupled to the detection modules and determines a false contour coefficient according to the feature coefficients. The false contour reduction circuit is coupled to the determination module of the false contour detection circuit to receive the false contour coefficient and perform false contour reduction on the image input signal according to the false contour coefficient, so as to output a corresponding image output signal.