Open Access

ARTICLE

Image Denoising Using a Nonlinear Pixel-Likeness Weighted-Frame Technique

P. Vinayagam^1,*, P. Anandan², N. Kumaratharan³

1 Department of ECE, Velammal Engineering College, Chennai, Tamilnadu, India
2 Department of ECE, C. Abdul Hakeem College of Engineering & Technology, Melvisharam, India
3 Department of ECE, Sri Venkateswara College of Engineering, Sriperumbudur, India

* Corresponding Author: P. Vinayagam. Email:

Intelligent Automation & Soft Computing 2021, 30(3), 869-879. https://doi.org/10.32604/iasc.2021.016761

Received 11 January 2021; Accepted 09 May 2021; Issue published 20 August 2021

Abstract

Recent advances in the development of image denoising applications for eliminating the various sources of noise in digital images have employed hardware platforms based on field programmable gate arrays for attaining speed and efficiency, which are essential factors in real-time applications. However, image denoising providing for maximum denoising performance, speed, and efficiency on these platforms is subject to constant innovation. To this end, the present work proposes a high-throughput fixed-point adaptive edge noise filter architecture to denoise digital images with additive white Gaussian noise in realtime using a nonlinear modified pixel-likeness weighted-frame technique. The proposed architecture works in two stages. The first stage involves normal and conditional sorting. The second stage is a decision-oriented output selection unit. Decision-oriented adaptive windowing is included for better impulse noise suppression and edge preservation. The denoising performance of the proposed denoising scheme is demonstrated to be superior to those currently available state-of-the-art approaches. Moreover, the power consumption is reduced by 25.01% compared to conventional algorithms.

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Keywords

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