On the Properties of Some Adaptive Morphological Filters for Salt and Pepper Noise Removal

IF 0.8 4区 计算机科学 Q4 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY Image Analysis & Stereology Pub Date : 2021-03-29 DOI:10.5566/IAS.2418
Marisol Mares-Javier, C. Guillén-Galván, R. Lemuz-López, J. Debayle
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引用次数: 3

Abstract

Mathematical Morphology (MM) is a tool that can be applied to many digital image processing tasks that include the reduction of impulsive or salt and pepper noise in grayscale images. The morphological filters used for this task are filters resulting from two basic operators: erosion and dilation. However, when the level of contamination of the image is higher, these filters tend to distort the image. In this work we propose a pair of operators with properties, that better adapt to impulsive noise than other classical morphological filters, it is demonstrated to be increasing idempotent morphological filters. Furthermore, the proposed pair turns out to be a Ʌ-filter and a V-filter which allow to build morphological openings and closings. Finally, they are compared with other filters of the state-of-the-art such as: SMF, PMSF, DBAIN, AMF and NAFSM, and have shown a better performance when the noise level is above 50%.
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几种用于椒盐噪声去除的自适应形态学滤波器的特性研究
数学形态学(MM)是一种可以应用于许多数字图像处理任务的工具,包括减少灰度图像中的脉冲或盐和胡椒噪声。用于此任务的形态滤波器是由两个基本算子:侵蚀和膨胀产生的滤波器。然而,当图像的污染程度较高时,这些过滤器往往会扭曲图像。在这项工作中,我们提出了一对具有比其他经典形态滤波器更能适应脉冲噪声的算子,并证明了它们是递增的幂等形态滤波器。此外,提出的配对结果是一个Ʌ-filter和一个v过滤器,允许建立形态学的开口和关闭。最后,将其与SMF、PMSF、DBAIN、AMF和NAFSM等最先进的滤波器进行了比较,在噪声水平大于50%时表现出更好的性能。
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来源期刊
Image Analysis & Stereology
Image Analysis & Stereology MATERIALS SCIENCE, MULTIDISCIPLINARY-MATHEMATICS, APPLIED
CiteScore
2.00
自引率
0.00%
发文量
7
审稿时长
>12 weeks
期刊介绍: Image Analysis and Stereology is the official journal of the International Society for Stereology & Image Analysis. It promotes the exchange of scientific, technical, organizational and other information on the quantitative analysis of data having a geometrical structure, including stereology, differential geometry, image analysis, image processing, mathematical morphology, stochastic geometry, statistics, pattern recognition, and related topics. The fields of application are not restricted and range from biomedicine, materials sciences and physics to geology and geography.
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