Open Access

ARTICLE

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

T. Manikandan¹, S. Karthikeyan^2,*, J. Jai Jaganath Babu³, G. Babu⁴

1 Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai, 602105, India
2 Department of Electronics and Communication Engineering, Velammal Institute of Technology, Chennai, 601204, India
3 Center for System Design, Chennai Institute of Technology, Chennai, 600069, India
4 Department of Bio-Medical Engineering, Easwari Engineering College, Chennai, 600089, India

* Corresponding Author: S. Karthikeyan. Email:

Intelligent Automation & Soft Computing 2023, 35(3), 2755-2771. https://doi.org/10.32604/iasc.2023.030497

Received 28 March 2022; Accepted 28 April 2022; Issue published 17 August 2022

Abstract

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 telemedicine. This article proposes a novel adaptive fuzzy filter based on the directionality 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. This filtering method comprises detection and filtering 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-suited filter for the specific image region, resulting in significant speckle noise suppression and retention of detailed features. The suggested approach uses a weighted average filter to distinguish between noise and edges at the filtering stage. In addition, we apply a structural similarity measure as a tuning parameter depending on the kind of noise in the ultrasound pictures. The proposed methodology shows that the proposed fuzzy adaptive filter effectively suppresses speckle noise while preserving edges and image detailed structures compared to existing approaches.

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Keywords

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