Paper Info
Title
Texture Enhanced Histogram Equalization Using Tv-L-1 Image Decomposition
Abstract
Histogram transformation defines a class of image processing operations that are widely applied in the implementation of data normalization algorithms. In this paper, we present a new variational approach for image enhancement that is constructed to alleviate the intensity saturation effects that are introduced by standard contrast enhancement (CE) methods based on histogram equalization. In this paper, we initially apply total variation (TV) minimization with a L-1 fidelity term to decompose the input image with respect to cartoon and texture components. Contrary to previous papers that rely solely on the information encompassed in the distribution of the intensity information, in this paper, the texture information is also employed to emphasize the contribution of the local textural features in the CE process. This is achieved by implementing a nonlinear histogram warping CE strategy that is able to maximize the information content in the transformed image. Our experimental study addresses the CE of a wide variety of image data and comparative evaluations are provided to illustrate that our method produces better results than conventional CE strategies.
Year
DOI
Venue
2013
10.1109/TIP.2013.2259839
IEEE TRANSACTIONS ON IMAGE PROCESSING
Keywords
DocType
Volume
Contrast enhancement, TV-L-1, image decomposition, histogram warping, entropy maximization
Journal
22
Issue
ISSN
Citations 
8
1057-7149
1
PageRank 
References 
Authors
0.35
15
3
Name
Order
Citations
PageRank
Ovidiu Ghita123418.12
Dana E Ilea2501.92
Paul F. Whelan356139.95