Video Contrast Control Using Histogram Translation Matrices
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Solution Overview
Problem
Video processing systems face challenges in increasing video image contrast while maintaining image quality, as spreading the dynamic range can amplify noise and degrade the image perceived by users.
Innovation Solution
A video processor that adjusts contrast by using a translation matrix based on current and previous video frames, employing histogram equalization and clipping techniques to redistribute luminance histogram points, thereby enhancing contrast without degrading the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the dynamic range of video pictures is spread to increase contrast, then the contrast of the video image is improved, but noise is amplified resulting in degradation of the video image
Solution Approach 1:
The patent applies preliminary action by performing noise filtering on the current video picture before generating the translation matrix for contrast enhancement. The filtering operation removes noise components from the picture data prior to the histogram equalization process, ensuring that subsequent contrast adjustments do not amplify these noise components. This preliminary noise removal step prevents the harmful effect of noise amplification while preserving the desired contrast enhancement.
Solution Approach 2:
The patent converts the harmful effect of noise amplification into a benefit by using the same spreading transformation to enhance both the signal and then selectively removing only the noise components. The filtering process exploits the statistical differences between noise and actual image content, preserving meaningful variations while eliminating noise. This transforms the potential harm of noise amplification into an opportunity for selective noise removal while maintaining contrast enhancement benefits.
2Productivity
If a translation matrix based solely on current picture is used, then the contrast adjustment is computationally simple, but the image quality degrades due to noise amplification
Solution Approach 1:
The patent performs noise filtering as a preliminary action before the main contrast enhancement processing. By filtering the current picture to remove noise components before generating the translation matrix, the system prevents noise amplification from occurring in the first place. This approach maintains computational efficiency while eliminating the harmful side effect, as the filtering operation is performed once on the original data rather than requiring complex iterative noise suppression during contrast adjustment.
3Illumination intensity
If histogram equalization is applied to enhance contrast, then the dynamic range is effectively utilized, but noise in uniform regions is amplified
Solution Approach 1:
The patent extracts and removes noise components from the video picture before applying histogram equalization. By separating the noise elements from the meaningful image content through filtering operations, the subsequent contrast enhancement process operates only on the cleaned signal. This extraction approach prevents noise in uniform regions from being amplified during the histogram equalization process, as the noise components have already been removed from the data being transformed.
Data Source
AI summary
A first video picture is translated based upon a first translation matrix to adjust a contrast of the first video image. A second translation matrix is determined based upon a first histogram of a second video picture. A third translation matrix is determined based upon the first translation matrix and the second translation matrix, and the video picture is translated based upon the third translation matrix. The translation matrix can be determined using a histogram that has been adjusted using a clipped histogram equalization technique.