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Adaptive Fuzzy Logic Despeckling in Non-Subsampled Contourlet Transformed Ultrasound Pictures

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摘要 Signal to noise ratio in ultrasound medical images captured through the digital camera is poorer,resulting in an inaccurate diagnosis.As a result,it needs an efficient despeckling method for ultrasound images in clinical practice and tel-emedicine.This article proposes a novel adaptive fuzzyfilter based on the direc-tionality and translation invariant property of the Non-Sub sampled Contour-let Transform(NSCT).Since speckle-noise causes fuzziness in ultrasound images,fuzzy logic may be a straightforward technique to derive the output from the noisy images.Thisfiltering method comprises detection andfiltering stages.First,image regions classify at the detection stage by applying fuzzy inference to the directional difference obtained from the NSCT noisy image.Then,the system adaptively selects the better-suitedfilter for the specific image region,resulting in significant speckle noise suppression and retention of detailed features.The suggested approach uses a weighted averagefilter to distinguish between noise and edges at thefiltering stage.In addition,we apply a structural similarity mea-sure as a tuning parameter depending on the kind of noise in the ultrasound pic-tures.The proposed methodology shows that the proposed fuzzy adaptivefilter effectively suppresses speckle noise while preserving edges and image detailed structures compared to existing approaches.
出处 《Intelligent Automation & Soft Computing》 SCIE 2023年第3期2755-2771,共17页 智能自动化与软计算(英文)
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