On the application of the reachability distance in the suppression of mixed Gaussian and impulsive noise in color images
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On the application of the reachability distance in the suppression of mixed Gaussian and impulsive noise in color images Bogdan Smolka1 · Damian Kusnik1 Received: 24 May 2019 / Revised: 2 July 2020 / Accepted: 6 August 2020 / © The Author(s) 2020
Abstract In this paper, we address the problem of mixed Gaussian and impulsive noise reduction in color images. A robust filtering technique is proposed, which is utilizing a novel concept of pixels dissimilarity based on the reachability distance. The structure of the denoising method requires the estimation of the impulsiveness of each pixel in the processing block using the introduced local reachability concept. Furthermore, we determine the similarity of each pixel in the block to the central patch consisting of the processed pixel and its neighbors. Both measures are calculated as an average of modified reachability distances to the most similar pixels of the central patch and the final filtering output is a weighted average of all pixels belonging to the processing block. The proposed technique was compared with widely used filtering methods and the performed experiments proved its satisfying denoising properties. The introduced filtering design is insensitive to outliers and their clusters introduced by the impulsive noise process, preserves details and is able to efficiently suppress the Gaussian noise while enhancing the image edges. Additionally, we proposed a method which estimates the noise contamination intensity, so that the proposed filter is able to adaptively tune its parameters. Keywords Noise · Color image enhancement · Impulsive noise · Gaussian noise · Mixed noise · Denoising · Reachability
1 Introduction In the recent years the topic of image denoising has been extensively studied in computer vision and digital image processing fields. The enhancement of image quality is a crucial Damian Kusnik
[email protected] Bogdan Smolka [email protected] 1
Faculty of Automatics, Electronics and Computer Science Akademicka 16, Silesian University of Technology, 44-100 Gliwice, Poland
Multimedia Tools and Applications
step for almost every computer vision system. Color digital images are often affected by various types of noise which can be caused by analog to digital converter errors during the acquisition process, transmission disturbances in noisy channels, malfunctioning pixels in the camera sensors, natural and man-made electromagnetic noise sources, aging of the storage material and flawed memory locations, among many others [3, 19, 41, 64]. As the denoising is the first step in the image processing pipeline, the effective restoration allows to successfully accomplish its further stages. Thus, denoising is one of the most significant low level processing operations. Generally, the noise filtering methods used for color image enhancement can be divided into component-wise and vector-based techniques. The component-wise filters process the color image channels independently, neglecting the usually strong inter-channel correlation. The advant
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