Title: Image denoising using discrete wavelet transform and adaptive thresholding optimised with improved arithmetic optimisation algorithm and guided filter

Authors: M. Mohana Dhas; N. Suresh Singh

Addresses: Department of Computer Science, Annai Velankanni College, Tholayavattam, India ' Department of Computer Applications, Malankara Catholic College, Mariagri, India

Abstract: The identification and characterisation of blood cells are needed for the diagnosis of blood-related diseases. To identify and classify different types of blood cells, image processing techniques are necessary. However, the medical images are generally corrupted with different types of noises. These noises affect the quality of images and causes impact in image processing. Denoising is a pre-processing method in image processing to acquire clear vision, eliminate noise, and enhance the quality of images. In this paper, a novel approach for medical image denoising based on discrete wavelet transform (DWT) and adaptive thresholding optimised with improved arithmetic optimisation algorithm and guided filter is proposed. Initially, the input image is denoised using DWT. Then, the denoised image is again processed with a guided filter for enhancing and improving the denoising performance. Moreover, from the experimental analysis, it is proven that the proposed approach provides better performance than the existing denoising methods.

Keywords: image denoising; blood cell images; discrete wavelet transform; DWT; arithmetic optimisation algorithm; AOA; guided filter.

DOI: 10.1504/IJCISTUDIES.2022.126898

International Journal of Computational Intelligence Studies, 2022 Vol.11 No.2, pp.131 - 156

Received: 12 May 2022
Accepted: 25 Jun 2022
Published online: 11 Nov 2022 *

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