期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 28, 期 5, 页码 2212-2227出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2018.2823424
关键词
Image process; image restoration; image enhancement; contrast enhancement; saturation enhancement; luminance enhancement; haze removal; fog; de-fog; haze; de-haze; dark channel prior; bilateral filter; wavelet transform; edge preserving; fast implement; color de-correlating
资金
- Ministry of Science and Technology [106-2221-E-011-149-MY2, 106-3114-E-011-008]
- One Hundred Talents Program 2012, Sichuan Province
Conventional haze-removal methods are designed to adjust the contrast and saturation, and in so doing enhance the quality of the reconstructed image. Unfortunately, the removal of haze in this manner can shift the luminance away from its ideal value. In other words, haze removal involves a tradeoff between luminance and contrast. We reformulated the problem of haze removal as a luminance reconstruction scheme, in which an energy term is used to achieve a favorable tradeoff between luminance and contrast. The proposed method bases the luminance values for the reconstructed image on statistical analysis of haze-free images, thereby achieving contrast values superior to those obtained using other methods for a given brightness level. We also developed a novel module for the estimation of atmospheric light using the color constancy method. This module was shown to outperform existing methods, particularly when noise is taken into account. The proposed framework requires only 0.55 s to process a one-megapixel image. Experimental results demonstrate that the proposed haze-removal framework conforms to our theory of contrast.
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