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Contrast Enhancement Based on Intrinsic Image Decomposition | IEEE Journals & Magazine | IEEE Xplore

Contrast Enhancement Based on Intrinsic Image Decomposition


Abstract:

In this paper, we propose to introduce intrinsic image decomposition priors into decomposition models for contrast enhancement. Since image decomposition is a highly illp...Show More

Abstract:

In this paper, we propose to introduce intrinsic image decomposition priors into decomposition models for contrast enhancement. Since image decomposition is a highly illposed problem, we introduce constraints on both reflectance and illumination layers to yield a highly reliable solution. We regularize the reflectance layer to be piecewise constant by introducing a weighted ℓ1 norm constraint on neighboring pixels according to the color similarity, so that the decomposed reflectance would not be affected much by the illumination information. The illumination layer is regularized by a piecewise smoothness constraint. The proposed model is effectively solved by the Split Bregman algorithm. Then, by adjusting the illumination layer, we obtain the enhancement result. To avoid potential color artifacts introduced by illumination adjusting and reduce computing complexity, the proposed decomposition model is performed on the value channel in HSV space. Experiment results demonstrate that the proposed method performs well for a wide variety of images, and achieves better or comparable subjective and objective quality compared with the state-of-the-art methods.
Published in: IEEE Transactions on Image Processing ( Volume: 26, Issue: 8, August 2017)
Page(s): 3981 - 3994
Date of Publication: 10 May 2017

ISSN Information:

PubMed ID: 28499999

Funding Agency:


References

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