Image Luminance Adjustment via Chrominance-Luminance Separation
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Solution Overview
Problem
Current image brightening methods in electronic devices enhance RGB values, leading to color distortion and loss of details in brightened regions, particularly affecting regions of interest like human faces.
Innovation Solution
An image processing method that traverses luminance components, generates a luminance distribution, and adjusts pixel values using a luminance mapping relation based on standard distributions for different scenes, ensuring image luminance improvement without color distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If RGB values are enhanced to brighten the image, then image luminance is improved, but color distortion occurs and details are lost
Solution Approach 1:
The patent segments the image processing into two independent parts: luminance processing and color processing. By operating only on the luminance channel (Y in YCbCr, or L in LAB) and leaving the color channels (CbCr or a*b*) unchanged, the method brightens the image while preserving color accuracy. This is achieved by converting to a color space with separate luminance and color components, adjusting only the luminance component using histogram equalization or mapping, and converting back to the original color space.
Solution Approach 2:
The patent extracts the luminance component from the image data, processes it separately to improve brightness, and then recombines it with the original color components. This extraction allows the luminance enhancement to be applied without affecting the color information, thereby resolving the contradiction between improving image luminance and maintaining color accuracy.
2Illumination intensity
If RGB values are enhanced to brighten the image, then image luminance is improved, but details in brightened regions are lost
Solution Approach 1:
By segmenting the processing to affect only the luminance channel and preserving the color channels intact, the method maintains edge information and detail structure while improving overall brightness. The color edges and fine details embedded in the color channels are not degraded by the luminance enhancement process.
Solution Approach 2:
The patent uses histogram analysis to understand the current luminance distribution and applies feedback-based adjustment through histogram equalization or mapping. This feedback mechanism ensures that the luminance enhancement is distributed optimally across different brightness regions, preserving details in both dark and bright areas while achieving overall image brightening.
Data Source
AI summary
An image processing method includes acquiring an image in a chrominance-luminance separation color mode; performing scene recognition of the image to determine a scene of the image; traversing luminance components of respective pixel points in the image, and generating a luminance distribution of the image according to a traversing result of the luminance components; generating a luminance mapping relation based on a standard luminance distribution corresponding to the scene of the image and the luminance distribution of the image; and adjusting the luminance components of the respective pixel points in the image according to the luminance mapping relation to generate a first processed image.