Retinex Image Enhancement with Brightness Gain Control
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Solution Overview
Problem
Existing image enhancement algorithms, such as Multi-scale Retinex and Multi-Scales Retinex with Color Restoration, are ineffective for images with multiple light sources, often producing halo artifacts and over-brightened outputs that do not accurately represent the real scene, especially in low-light conditions.
Innovation Solution
An image enhancement method using a Retinex image enhancement algorithm with a brightness gain control factor, computed based on the log average value of input brightness, to adjust pixel brightness values and control the overall brightness of the output image, ensuring it aligns with the real environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Multi-scale Retinex or MSR with Color Restoration algorithms are used for image enhancement, then color fidelity and detail enhancement are improved, but halo artifacts are generated and output brightness becomes inconsistent with real scene
Solution Approach 1:
The patent modifies the Retinex algorithm by changing the brightness gain computation parameters. Instead of using fixed or simple adaptive brightness gain, the patent computes brightness gain based on the average brightness of the input image, creating a dynamic parameter adjustment mechanism that adapts to different lighting conditions and prevents halo artifacts while maintaining detail enhancement.
2Measurement precision
If Retinex algorithm is used to enhance dark images, then image clarity is improved, but output image becomes over bright and does not match real scene
Solution Approach 1:
The patent implements a feedback mechanism where the brightness gain is computed based on the average brightness of the input image. This creates a closed-loop system where the enhancement strength automatically adjusts according to the input image's lighting conditions, preventing over-brightening while maintaining clarity improvement for dark images.
Solution Approach 2:
The patent transforms the static brightness gain approach into a dynamic one by computing brightness gain as a function of input image brightness. This allows the algorithm to adaptively adjust enhancement strength based on real-time input characteristics, ensuring output brightness remains consistent with the real scene across varying lighting conditions.
Data Source
AI summary
The present application provides an image enhancement method and system, the method includes acquiring an input brightness value, and computing a log average value of the input brightness value; processing the input image based on a Retinex image enhancement algorithm to obtain a first brightness gain value; computing a brightness gain control factor according to the log average value of the input brightness value; computing a second brightness gain value according to the brightness gain control factor and the first brightness gain value; and obtaining an output image by enhancing the input image according to the second brightness gain value. The present application uses a Retinex image enhancement algorithm to enhance the input image, and by using the brightness gain control factor, when the image has low brightness, the first brightness gain value is compressed, and when the image has high brightness, the first brightness gain value is compressed slightly.