A novel edge preserving filter for impulse noise removal

Abstract

This paper proposes an edge preserving filter for removal of impulse noise. Digital images received from various sources are often degraded due to impulse noise and thus become unsuitable for further processing. To overcome this degradation removal of impulse noise is very important. In this paper an effective and efficient method of impulse noise removal is proposed which not only removes noise but also preserves edges. The algorithm first finds noisy, noise free and edge pixels. Then it replaces the noisy pixel with a pixel from its neighbourhood which is nearest to the adaptive median of the noisy pixel, this removes the noise as well as preserves edges and fine image details.

High quality impulse noise removal via non‐uniform sampling and autoregressive modelling based super‐resolution

“…Recently, some researchers realised that different kinds of 2D image features can be used for better restoring performance. Therefore, edge preserving and direction based filters gained more and more attention [11–15]. Recent years, some interpolation based denoising algorithm, such as [16, 17], also yielded significant denoising results.…”

“…In fact, as we all know, in many cases of image processing, the performance of an algorithm primarily depends on its adaptability to varying structures across an image [18]. In impulse noise removal, the methods in [11–15] took some 2D image features such as edge, gradient and direction information into account and achieved exciting experimental results. However, in impulse noise removal processing, it is difficult to effectively extract and make full use of image structure because of the absence of massive randomly located pixels. The most common way to remove impulse noise is to perform different kinds of algorithms on a sliding window to calculate the value of the centred noisy pixel.…”

A Novel Algorithm for Impulse Noise Removal and Edge Detection

“…The main morphological edge detection methods are morphological residual edge detection, top-hat method, ASF method [7], multi-scale method [8] and multi-grade method [9]. Salt-and-pepper impulse noise is one commonly encountered noise type during image and video communication [10].Salt and Pepper noise can be removed by Progressive Switching Median (PSM) filter [11], Extremum Median (EM) filter [12], Adaptive Median (AM) filter [13] and Weighted Median (WM) filter [14] and some other methods like those in [15,16,21,22]. Edge detection of noisy images is one of the challenging task in the field of image processing ,the literature survey shows that a number of algorithms have been proposed for this like [17] uses a separate wavelet based noise reduction block for preprocessing before edge detection.…”