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논문 기본 정보

자료유형
학술저널
저자정보
Eunsung Lee (Chung-Ang University) Wonseok Kang (Chung-Ang University) Sangjin Kim (Chung-Ang University)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEEK Transactions on Smart Processing & Computing Vol.1 No.1
발행연도
2012.8
수록면
8 - 16 (9page)

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초록· 키워드

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An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

목차

Abstract
1. Introduction
2. Fundamentals of Contrast Enhancement Using Histogram
3. Low-exposure Image Enhancement based on Adaptive Transfer Function Estimation and Histogram Specification Using Image Analysis
4. Color Shift Model-based Refocusing using Color Enhancement for Low-exposure Images based on Histogram Specification
5. Experimental Results
6. Conclusion
References

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