Adaptive tone-preserved image detail enhancement
Yun Ling, Caiping Yan, Chunxiao Liu, Xun Wang, Hong Li
In The Visual Computer, 28(6--8), June 2012.
Abstract: An adaptive tone-preserved algorithm for image detail enhancement is proposed to retain the tonal distribution of the input image and avoid experiential manipulation. First of all, domain transform based multi-scale image decomposition is carried out to quickly divide the input image into a base image which contains the coarse-scale image information, and the detail layers which contain the fine-scale details. Then, during the process of detail enhancement and synthesis, we construct an adaptive detail enhancement function based on the edge response, to prevent the exaggeration of strong edges and increase the enhancing magnitude of small details. Finally, in order to keep the color values of the input image and the gradient values of the detail enhanced image, a tonal correction algorithm based on energy optimization is presented to eliminate the distinct tonal differences of the enhanced image from the input image. Our experimental results show that tone-consistent image detail enhancement effect is available for arbitrary input images with unified parameters setting, which is superior to the state-of-the-art methods.
@article{Ling:2012:ATI,
author = {Yun Ling and Caiping Yan and Chunxiao Liu and Xun Wang and Hong Li},
title = {Adaptive tone-preserved image detail enhancement},
journal = {The Visual Computer},
volume = {28},
number = {6--8},
pages = {733--742},
month = jun,
year = {2012},
}
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