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Medical Image Enhancement Based on Shearlet Transform and Unsharp Masking

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Due to the noisy nature of medical images, enhancement processing is often desired to extract information from those images. In this paper, we proposed a novel enhancement algorithm for medical image processing based on Shearlet transform and unsharp masking. There are four steps in this algorithm. First, histogram equalization is applied to the medical image; Second, the medical image is decomposed into low frequency component and high frequency component using shearlet transform. Third, the adaptive threshold denoising and linear enhancement is applied to the high frequency components while the low frequency components are not processed; Lastly, the coefficients are increased through unsharp masking algorithm behind the Shearlet inverse transform process. The benchmark results for this algorithms showed that the proposed method could significantly enhance the medical images and thus improve the image qualities.
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Keywords: HISTOGRAM EQUALIZATION; MEDICAL IMAGE; SHEARLET TRANSFORM; UNSHARP MASKING

Document Type: Research Article

Publication date: 01 October 2014

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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