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Visualizing Visual Adaptation

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Published on: April 24, 2017

Contrast-dependent saturation adjustment for outdoor image enhancement.

Shuhang Wang, Woon Cho, Jinbeum Jang

Journal of the Optical Society of America. A, Optics, Image Science, and Vision

|January 7, 2017

Summary

This study introduces a new image enhancement method for outdoor photos suffering from poor visibility. The content-adaptive approach improves contrast and color saturation, outperforming existing techniques.

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Area of Science:

Computer Vision
Image Processing
Digital Photography

Background:

Outdoor images in adverse weather conditions often exhibit reduced contrast and color saturation due to light scattering and attenuation.
Existing image enhancement techniques frequently lack generalizability, performing well on limited image sets but failing on diverse datasets.

Purpose of the Study:

To develop a robust image enhancement method for improving the quality of outdoor images captured in poor weather.
To address the limitations of current methods by proposing a technique that enhances both intensity contrast and color saturation adaptively.

Main Methods:

A novel content-adaptive histogram equalization method, inspired by the human visual system, is proposed to enhance image intensity contrast.
A contrast-dependent saturation adjustment prior is introduced to refine color saturation based on the improved intensity contrast.

Main Results:

The proposed method demonstrated superior performance in enhancing image visibility and preserving naturalness compared to eight state-of-the-art enhancement and haze removal techniques.
Experimental results validated the method's effectiveness across various types of challenging outdoor images.

Conclusions:

The developed image enhancement technique offers a significant improvement for outdoor photography in adverse conditions.
The combination of content-adaptive contrast enhancement and contrast-dependent saturation adjustment provides a more effective and natural-looking image quality improvement.