Automatic Brightness Adjustment Using Histogram Equalization
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Solution Overview
Problem
Current automatic brightness adjustment methods, such as automatic exposure (AE) and histogram equalization (HE), are insufficient in enhancing image contrast and can result in unnatural image distortions, especially when brightness is intensively distributed, and require complex calculations that degrade hardware performance.
Innovation Solution
An automatic brightness adjusting method and apparatus using a histogram equalization scheme based on cumulative distribution functions and inverse cumulative distribution functions, which generate a conversion function to apply histogram equalization to input images, improving contrast without unnatural distortions and reducing computational load by using look-up tables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If histogram equalization is applied to improve contrast, then brightness distribution is equalized, but the image may be distorted in an unnatural manner
Solution Approach 1:
The patent applies different processing strategies to different regions of the histogram based on the input image's brightness distribution characteristics. When brightness is concentrated in the lower band, HE is applied; when concentrated in the upper band, brightness preservation is prioritized. This local adaptation to different brightness conditions resolves the contradiction between achieving uniform brightness distribution and maintaining image naturalness.
2Reliability
If complex algorithms like BBHE or DSIHE are used to supplement HE drawbacks, then image naturalness is improved, but calculation complexity increases and hardware performance deteriorates
Solution Approach 1:
The patent changes the parameter of algorithm selection based on the brightness distribution characteristics of the input image. By detecting whether brightness is concentrated in the lower or upper band and selecting different processing modes accordingly, the system achieves both image naturalness and computational efficiency without requiring complex algorithms like BBHE or DSIHE.
Solution Approach 2:
The patent uses a simplified approach that copies the essential functionality of complex algorithms (brightness preservation in appropriate regions) without implementing their full complexity. By using conditional HE application based on histogram analysis, it achieves similar results to complex algorithms with much lower computational overhead.
3Illumination intensity
If AE calculates average brightness and adjusts gain, then overall brightness is optimized, but contrast improvement is insufficient when brightness is intensively distributed
Solution Approach 1:
The patent merges the advantages of both AE and HE by first using AE to optimize overall brightness and then conditionally applying HE to improve contrast when brightness is intensively distributed. This combination allows the system to achieve both optimal overall brightness and improved contrast quality simultaneously.
Data Source
AI summary
An automatic brightness adjusting method and apparatus for image signal processor (ISP) is provided. The image processing apparatus may include a histogram generating unit, a cumulative distribution function calculator, and a histogram equalization (HE) unit. The histogram generating unit may generate a histogram of brightness values of pixels in an input image. The cumulative distribution function calculator may generate a cumulative distribution function and an inverse cumulative distribution function, based on the generated histogram. The HE unit may generate a conversion function based on the cumulative distribution function and the inverse cumulative distribution function, and may apply HE to the input image based on the conversion function so as to generate an output image.