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Performance Assessment of Edge Preserving Filters

Kamireddy Rasool Reddy (JNTU Kakinada, Kakinada, India), Madhava Rao Ch (Sir C.R. Reddy College of Engineering, Vijayawada, India) and Nagi Reddy Kalikiri (NBKR Institute of Science and Technology, Vidyanagar, India)

Source Title: International Journal of Information System Modeling and Design (IJISMD) 8(2)

DOI: 10.4018/IJISMD.2017040101

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Abstract

Denoising is one of the important aspects in image processing applications. Denoising is the process of eliminating the noise from the noisy image. In most cases, noise accumulates at the edges. So that prevention of noise at edges is one of the most prominent problem. There are numerous edge preserving approaches available to reduce the noise at edges in that Gaussian filter, bilateral filter and non-local means filtering are the popular approaches but in these approaches denoised image suffer from blurring. To overcome these problems, in this article a Gaussian/bilateral filtering (G/BF) with a wavelet thresholding approach is proposed for better image denoising. The performance of the proposed work is compared with some edge-preserving filter algorithms such as a bilateral filter and the Non-Local Means Filter, in terms that objectively assess quality. From the simulation results, it is found that the performance of proposed method is superior to the bilateral filter and the Non-Local Means Filter.

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2. Edge Preserving Filters

This section reviews the various edge preserving filtering methodologies such as Gaussian filter and bilateral filter. The main scope of this paper is reducing the noise presents at edges to some large extent.

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Performance Assessment of Edge Preserving Filters

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2. Edge Preserving Filters

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