Image Contrast Enhancement Using Histogram Valley Stretching
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Solution Overview
Problem
Low-contrast environments, such as nighttime driving or industrial settings, hinder human and machine visibility, leading to safety and operational challenges due to inadequate illumination and glare.
Innovation Solution
A computer-based system that enhances image contrast by analyzing pixel values and applying contrast metrics to adjust pixel brightness, using histograms and heuristics to create an enhanced image, which can include infrared illumination for improved visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If standard headlights are used to illuminate the road at night, then visibility is improved to some extent, but glare from headlights creates harmful effects that reduce visibility
Solution Approach 1:
The patent segments the image processing into multiple stages: capturing the original image, generating a contrast metric, creating a histogram, identifying peaks and valleys, and applying selective pixel value adjustments. This segmentation allows the system to address different regions and intensity levels independently, improving road illumination while controlling glare through localized processing.
Solution Approach 2:
The patent applies local quality by using histogram analysis to identify specific pixel value ranges (peaks and valleys) and applying different enhancement strategies to different regions of the image. The contrast enhancement is applied selectively based on local histogram characteristics rather than uniformly across the entire image, allowing optimal illumination enhancement while preserving detail in both dark and bright regions.
2Illumination intensity
If image brightness is increased to improve visibility in low-contrast environments, then contrast is enhanced, but noise and artifacts may be amplified
Solution Approach 1:
The patent employs dynamic contrast enhancement by calculating a contrast metric and using histogram analysis that adapts to the specific characteristics of each image. The peak and valley identification in the histogram allows the system to dynamically determine the optimal enhancement parameters for each image, rather than applying a fixed enhancement algorithm. This dynamic approach enhances brightness while preserving image quality by adapting to the actual distribution of pixel values.
Solution Approach 2:
The patent implements feedback through the contrast metric calculation and histogram analysis. The system continuously evaluates the image quality metrics, identifies peaks and valleys in the histogram, and uses this feedback information to guide the contrast enhancement process. This feedback mechanism ensures that enhancement is applied appropriately to improve visibility while avoiding excessive amplification of noise and artifacts.
Data Source
AI summary
A system and method for enhancing the contrast within an image. An enhanced image can be generated in a real-time or substantially real-time manner from an initial image. The pixel values of the initial image can be used to populate a histogram or otherwise serve as the basis for subsequent processing. A valley can be identified within the range of pixel values for use as a stretch metric used by a stretch heuristic to expand the contrast of the pixel values in the initial image by expanding the range of pixel values associated with the pixels in the histogram. In some embodiments, the initial image is first divided into image regions that are each associated with individualized processing. A bilinear interpolation step can then be performed to smooth the integrated image after the individualized processing is used to stretch the pixels within the individual image regions.