期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2017
卷号：8
期号：4
页码：1
DOI：10.5121/sipij.2017.8401
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Ultrasonograms refer to images generated through ultrasonography, a technique that applies ultrasoundpulses to delineate internal structures of the body. Despite being useful in medicine, ultrasonograms usuallysuffer from multiplicative noises that may limit doctors to analyse and interpret them. Attempts to address thechallenge have been made from previous works, but denoising ultrasonograms while preserving semanticfeatures remains an open-ended problem. In this work, we have proposed a diffusion-steered model thatgives an effective interplay between total variation and Perona-Malik models. Two parameters have beenintroduced into the framework to convexify our energy functional. Also, to deal with multiplicative noise, wehave incorporated a log-based prior into the framework. Empirical results show that the proposed methodgenerates sharper and detailed images. Even more importantly, our framework can be evolved over a longertime without smudging critical image features.
关键词：Denoising; ultrasound image; optimization; Perona-Malik; total variation
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