Title: Multi-resolution transform-based image denoising and fusion for Poisson noise suppression

Authors: D. Mary Sugantharathnam; D. Manimegalai; T. Jayasree

Addresses: Government College of Engineering, Tirunelveli 7, Tamil Nadu, India ' National Engineering College, Kovilpatti, Tamil Nadu, India ' Government College of Engineering, Tirunelveli 7, Tamil Nadu, India

Abstract: Noise removal is essential in medical imaging applications in order to enhance and recover anatomical details that may be hidden in the data. The issues of Poisson noise occurrence in medical imaging due to the arrival of photon nature of light produced at the time of capturing of image have always been a concern. This paper addresses a novel approach for the removal of Poisson noise embedded in the biomedical images based on multi-resolution transform-based denoising and fusion approach. In this technique, first, the images are denoised separately, by applying Discrete Wavelet Transform (DWT)/Stationary Wavelet Transform (SWT) and Fast Discrete Curvelet Transform (FDCT) integrated with Rudin-Osher-Fatemi (ROF) model. Next, the distinct features extracted from the denoised images are fused, resulting in an enhanced and denoised image. The proposed method was tested and compared with other denoising techniques on a set of biomedical images. Subjective and objective evaluations show better performance of this new approach compared to existing techniques.

Keywords: wavelet transform; curvelet transform; Poisson noise; denoising; biomedical imaging.

DOI: 10.1504/IJBET.2018.095207

International Journal of Biomedical Engineering and Technology, 2018 Vol.28 No.3, pp.273 - 285

Received: 20 Apr 2016
Accepted: 31 Aug 2016
Published online: 02 Oct 2018 *

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