Contrast enhancement for image by WNN and GA combining PSNR with information entropy
Fuzzy Optimization and Decision Making
IEICE - Transactions on Information and Systems
Objective Quality Assessment Measurement for Typhoon Cloud Image Enhancement
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Engineering Applications of Artificial Intelligence
A variational approach for exact histogram specification
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Exact Histogram Specification for Digital Images Using a Variational Approach
Journal of Mathematical Imaging and Vision
Fully Smoothed ℓ1-TV Models: Bounds for the Minimizers and Parameter Choice
Journal of Mathematical Imaging and Vision
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Histogram specification (equalization) is an important tool for tasks such as image enhancement and normalization. Although this problem has exact solution for continuous images, in the case of digital images, it is ill posed. Recently, an exact pixel ordering method based solely on local image intensity was proposed, yet still with some limitations, especially since it ignores the important image edge information. In this paper, we present a wavelet-based method that simultaneously achieves the exact histogram specification and good image enhancement performance. It does so through a carefully designed strict pixel ordering process, during which the wavelet coefficients are fine tuned for the image enhancement purpose. Compared to previous work, this approach takes into account not only local mean intensity values, but also local edge information. Other advantages include fast pixel ordering, good statistical models, and better image enhancement performance. Experimental results and comparison with state-of-the-art methods are presented.