Image Enhancement Under Gaussian Impulse Noise for Satellite and Medical Applications

Author:

Aetesam Hazique1,Maji Suman Kumar1,Boulanger Jerome2

Affiliation:

1. Indian Institute of Technology, Patna, India

2. MRC Laboratory of Molecular Biology, Cambridge, UK

Abstract

Remote sensing technologies such as hyperspectral imaging (HSI) and medical imaging techniques such as magnetic resonance imaging (MRI) form the pillars of human advancement. However, external factors like noise pose limitations on the accurate functioning of these imaging systems. Image enhancement techniques like denoising therefore form a crucial part in the proper functioning of these technologies. Noise in HSI and MRI are primarily a mixture of Gaussian and impulse noise. Image denoising techniques designed to handle mixed Gaussian-impulse (G-I) noise are thus an area of core research under the field of image restoration and enhancement. Therefore, this chapter discusses the mathematical preliminaries of G-I noise followed by an elaborate literature survey that covers the evolution of image denoising techniques for G-I noise from filtering-based to learning-based. An experimental analysis section is also provided that illustrates the performance of several denoising approaches under HSI and MRI, followed by a conclusion.

Publisher

IGI Global

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. CompoHyDen: Hyperspectral Image Restoration via Nonconvex Componentwise Minimization;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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