Multiple layers block overlapped histogram equalization for local content emphasis
Computers and Electrical Engineering
Visual impact enhancement via image histogram smoothing and continuous intensity relocation
Computers and Electrical Engineering
A variational approach for exact histogram specification
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Iterative thresholding based partially overlapped sub-block bi-histogram equalization
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Entropy-based histograms for selectivity estimation
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Exact Histogram Specification for Digital Images Using a Variational Approach
Journal of Mathematical Imaging and Vision
The Visual Computer: International Journal of Computer Graphics
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Histogram equalization (HE) is a simple and effective image enhancing technique, however, it tends to change the mean brightness of the image to the middle level of the permitted range, and hence is not very suitable for consumer electronic products, where preserving the original brightness is essential to avoid annoying artifacts. This paper proposes a novel extension of histogram equalization, actually histogram specification, to overcome such drawback as HE. To maximize the entropy is the essential idea of HE to make the histogram as flat as possible. Following that, the essence of the proposed algorithm, named brightness preserving histogram equalization with maximum entropy (BPHEME), tries to find, by the variational approach, the target histogram that maximizes the entropy, under the constraints that the mean brightness is fixed, then transforms the original histogram to that target one using histogram specification. Comparing to the existing methods including HE, brightness preserving bi-histogram equalization (BBHE), equal area dualistic sub-image histogram equalization (DSIHE), and minimum mean brightness error bi-histogram equalization (MMBEBHE), experimental results show that BPHEME can not only enhance the image effectively, but also preserve the original brightness quite well, so that it is possible to be utilized in consumer electronic products.