Shadow Area Luminance Compensation via Local Pixel Analysis
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Solution Overview
Problem
Existing image processing techniques fail to effectively enhance luminance in shadow areas while maintaining clarity in non-shadow areas, as they uniformly increase luminance across all pixels regardless of their location, leading to distorted images and difficulty in distinguishing objects in dark regions.
Innovation Solution
A method that analyzes spatial luminance by dividing images into regions, calculates representative luminance considering neighboring pixels, and applies an exponential curve using T- and G-parameters to selectively increase luminance in dark areas, preventing unwanted luminance increases in bright areas, thereby improving image clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If uniform luminance compensation is applied to all pixels regardless of their position, then the luminance of pixels in dark areas is improved, but the luminance of pixels in bright areas is also increased causing distortion and loss of natural appearance
Solution Approach 1:
The patent applies different luminance compensation strategies to different spatial regions of the image. Pixels in dark areas (where local luminance is below a threshold) receive enhanced luminance compensation, while pixels in bright areas maintain their original luminance characteristics. This is achieved by calculating local luminance for each pixel and applying conditional compensation only where needed, thereby improving visibility in shadow regions without distorting bright regions.
2Productivity
If luminance compensation is applied without considering neighboring pixels, then processing speed is maintained, but the luminance of each pixel does not reflect the luminances of pixels positioned in the vicinity causing uneven compensation
Solution Approach 1:
The patent segments the image processing into distinct stages: first calculating local luminance for each pixel based on neighboring pixels, then comparing against a threshold to determine compensation eligibility, and finally applying selective luminance enhancement. This segmented approach allows the system to incorporate spatial information from neighboring pixels for accurate local luminance assessment while maintaining processing efficiency through optimized calculation sequences and early termination conditions.
3Loss of information
If overall luminance compensation is applied to the entire image, then visibility in dark areas is improved, but the overall contrast and natural appearance of the image is degraded
Solution Approach 1:
The patent dynamically adjusts the luminance compensation parameter based on local image characteristics. For each pixel, the system calculates local luminance and selectively applies compensation only when the local luminance falls below a predetermined threshold. This parameter-based selective compensation preserves the natural contrast relationships in the image while enhancing visibility in genuinely dark regions, avoiding the blanket over-brightening effect of overall luminance compensation.
Data Source
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AI summary
An image compensating system, medium, and method, including, a shadow area compensating system, medium, and method which may significantly increase the luminance of each pixel in a dark area with respect to pixels positioned in the vicinity of the corresponding pixel and slightly increase the luminance of each pixel in a bright area. The shadow area compensating method includes calculating a representative luminance Lav of each pixel having image information by reflecting the luminance of the corresponding pixel and the luminances of pixels positioned in the vicinity of the corresponding pixel, determining a compensation luminance ratio using the calculated representative luminance, and increasing an output luminance on the basis of the compensation luminance ratio.