Image Processing Apparatus Mist Distribution Correction
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Solution Overview
Problem
Existing image processing techniques fail to effectively improve visibility in images with both mist and non-mist regions, often resulting in unnatural contrast corrections and irregular brightness due to varying correction strengths across local areas.
Innovation Solution
An image processing apparatus and method that estimates the density of the mist component and performs gradation correction based on its distribution, switching between adaptive and uniform contrast correction methods to maintain natural image quality and improve visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If adaptive contrast correction is performed for each local area, then contrast improvement is enhanced in mist regions, but unnatural brightness irregularities and stepwise gradation changes occur at boundaries
Solution Approach 1:
The patent applies dynamics by making the correction method adaptable based on image characteristics. The system dynamically determines whether to apply local area correction or entire image correction based on the standard deviation of brightness values, allowing the correction approach to change according to the specific image conditions rather than being fixed.
Solution Approach 2:
The patent changes the parameter of correction scope from local areas to entire image based on image analysis. By calculating the standard deviation of brightness values and comparing it to a threshold, the system switches between different correction parameters (local vs. global), resolving the contradiction between contrast improvement and brightness uniformity.
2Stability of the object's composition
If contrast correction is performed uniformly across the entire image, then brightness uniformity is maintained, but contrast improvement is insufficient in images with both mist and non-mist regions
Solution Approach 1:
The system dynamically adjusts the correction strategy based on image characteristics. When the standard deviation of brightness values exceeds a threshold (indicating mixed mist and non-mist regions), the system switches from uniform entire image correction to local area correction, thereby improving contrast where needed while maintaining uniformity where applicable.
Solution Approach 2:
The patent changes the correction scope parameter from entire image to local areas based on the calculated standard deviation. This parameter switching allows the system to optimize between uniformity and contrast improvement by selecting the appropriate correction scope based on image analysis.
3Measurement precision
If local area correction is applied throughout, then contrast is improved in mist regions, but correction strength varies excessively between local areas causing unnatural appearance
Solution Approach 1:
The patent applies dynamics by making the correction strategy adaptive rather than static. The system dynamically evaluates image characteristics (standard deviation of brightness) and adjusts the correction approach accordingly, switching between local and global correction to maintain natural appearance while improving contrast where necessary.
Solution Approach 2:
The system changes the correction parameter from consistent local area correction to conditional correction (local or entire image based on standard deviation). This parameter change prevents excessive variation in correction strength by selecting the appropriate correction scope, thereby maintaining natural image appearance while achieving effective contrast improvement.
Data Source
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Figure 3A~3B
AI summary
An image processing apparatus includes a degree-of-degradation detector (200), a degree-of-degradation estimation unit (201), a correction system selector (202) and a gradation correction unit (110, 111). The degree-of-degradation detector (200) detects a degree of degradation of an image. The degree-of-degradation estimation unit (201) estimates a distribution of the degree of degradation in the image. The correction system selector (202) selects either a first gradation correction system or a second gradation correction system in accordance with the distribution of the degree of degradation. The gradation correction unit (110, 111) performs gradation correction of the image based on either the selected first or second gradation correction system.