Image Contrast Enhancement via Local Histogram Weighting
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Solution Overview
Problem
Existing image processing systems struggle to effectively improve contrast in images captured in poor lighting conditions, such as backlight or low light environments, often resulting in low brightness and poor contrast, and may introduce flickering issues with local histogram equalization methods.
Innovation Solution
The proposed solution involves an image processing device that splits images into multiple regions, calculates histograms for these regions, generates contrast conversion functions based on the histograms, and converts the contrast of pixels by considering adjacent regions, using weights calculated from the distances between pixel centers and adjacent region centers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If global functions such as gamma are used to increase brightness, then brightness is improved, but contrast is lowered
Solution Approach 1:
The image is divided into multiple local regions, and histogram equalization is applied independently to each region rather than globally. This segmentation allows brightness enhancement in dark areas while preserving local contrast characteristics, resolving the trade-off between brightness and contrast improvement
Solution Approach 2:
Different processing parameters and contrast conversion functions are applied to different local regions based on their specific characteristics. Each region receives customized contrast enhancement tailored to its local brightness and histogram distribution, maintaining contrast quality while improving overall brightness
2Manufacturing precision
If local histogram equalization method is used, then contrast is improved, but flickering problems occur
Solution Approach 1:
The patent combines multiple contrast conversion functions from adjacent regions through weighted averaging. This merging approach smooths out abrupt brightness transitions between regions, eliminating flickering effects while maintaining local contrast enhancement benefits
Solution Approach 2:
The patent incorporates feedback mechanisms by considering histogram changes between frames and adjusting contrast conversion functions accordingly. This feedback loop detects and compensates for significant histogram variations, preventing flickering caused by frame-to-frame fluctuations
3Manufacturing precision
If histogram equalization is applied to each region independently, then local contrast is improved, but brightness becomes unstable when histogram changes significantly
Solution Approach 1:
The patent dynamically adjusts contrast conversion functions based on real-time histogram analysis and frame-to-frame changes. When significant histogram changes are detected, the system adapts its processing parameters to maintain brightness consistency, making the contrast enhancement stable and flicker-free
Data Source
AI summary
The present disclosure relates to an image processing device to which contrast improvement effect may be applied, an image processing system, and a method of operating the same. An example method of operating an image processing device includes receiving an image including a plurality of pixels, splitting the image into a plurality of first regions, calculating a histogram for a second region that is greater than a first region of the plurality of first regions, generating a contrast conversion function based on the histogram for each of the plurality of first regions, and converting contrast of a current pixel among the plurality of pixels based on M×M first regions among the plurality of first regions adjacent to the current pixel. M is a natural number greater than or equal to 2.