Microscopy mineral image enhancement based on improved adaptive threshold in nonsubsampled shearlet transform domain

In this paper, a novel microscopy mineral image enhancement method based on adaptive threshold in non-subsampled shearlet transform (NSST) domain is proposed. First, the image is decomposed into one low-frequency sub-band and several high-frequency sub-bands. Second, the gamma correction is applied...

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Bibliographic Details
Main Authors: Liangliang Li, Yujuan Si, Zhenhong Jia
Format: Article
Language:English
Published: AIP Publishing LLC 2018-03-01
Series:AIP Advances
Online Access:http://dx.doi.org/10.1063/1.4998400
Description
Summary:In this paper, a novel microscopy mineral image enhancement method based on adaptive threshold in non-subsampled shearlet transform (NSST) domain is proposed. First, the image is decomposed into one low-frequency sub-band and several high-frequency sub-bands. Second, the gamma correction is applied to process the low-frequency sub-band coefficients, and the improved adaptive threshold is adopted to suppress the noise of the high-frequency sub-bands coefficients. Third, the processed coefficients are reconstructed with the inverse NSST. Finally, the unsharp filter is used to enhance the details of the reconstructed image. Experimental results on various microscopy mineral images demonstrated that the proposed approach has a better enhancement effect in terms of objective metric and subjective metric.
ISSN:2158-3226