Topic
Impulse noise
About: Impulse noise is a research topic. Over the lifetime, 4816 publications have been published within this topic receiving 63970 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: Experimental studies show that the proposed technique is simple, easy to implement, robust to noise, and outperforms the classic vector filters, as well as more recent filters.
Abstract: This research presents a complete study of a new alternating vector filter for the removal of impulsive noise in colour images. The method is based on an impulsive noise detector for greyscale images that has been adapted in a localised manner using geometric information for processing colour images. Based on this statistic, a filtering scheme alternating between the identity and a non-linear vector filter is proposed. A geometric and experimental study was performed to obtain the optimal filter design. Experimental studies show that the proposed technique is simple, easy to implement, robust to noise, and outperforms the classic vector filters, as well as more recent filters.
16 citations
TL;DR: An algorithm based on radial basis functions (RBF) interpolation which estimates the intensities of corrupted pixels by their neighbors using RBFs can effectively remove the highly dense impulse noise.
Abstract: Preserving details while restoring images highly corrupted by impulsive salt and pepper noise remains a challenging problem. The authors proposed an algorithm based on radial basis functions (RBFs) interpolation which estimates the intensities of corrupted pixels by their neighbours. In this algorithm, intensity values of noisy pixels in the corrupted image are first estimated using RBFs. Next, the image is smoothed. The proposed algorithm can effectively remove the highly dense, impulsive salt and pepper noise. Experimental results show the superiority of the proposed algorithm both in noise suppression and details preservation in comparison to the recent similar methods. Extensive simulations show better results measured by peak signal-to-noise ratio and structural similarity index, especially when the image is corrupted by very highly dense impulse noise.
16 citations
23 Jul 2007
TL;DR: Experimental results show that the proposed operator exhibits superior performance over the competing operators and is capable of efficiently suppressing the noise in the image while at the same time effectively preserving the useful information in theimage.
Abstract: A novel filtering operator based on type-2 fuzzy logic techniques is proposed for detail preserving restoration of impulse noise corrupted images. The performance of the proposed operator is tested for different test images corrupted at various noise densities and also compared with representative conventional as well as state-of-the-art impulse noise removal operators from the literature. Experimental results show that the proposed operator exhibits superior performance over the competing operators and is capable of efficiently suppressing the noise in the image while at the same time effectively preserving the useful information in the image.
16 citations
23 May 2005
TL;DR: A new detector of random-valued impulse noise in images using level detection that reduces undetected noise pixels without increasing mis-detections and performs significantly better than conventional methods.
Abstract: We propose a new detector of random-valued impulse noise in images using level detection. In our method, we use directional windows in order to search a level region in the images. One window, whose variation is lowest, is selected as a flat window from multi directional windows. In a flat window, random-valued impulse noise may move to both ends of the order statistics. Therefore, noise detection in the selected window is easy. Consequently, the proposed method reduces undetected noise pixels without increasing mis-detections. Extensive simulations indicate that the proposed method performs significantly better than conventional methods.
15 citations
TL;DR: An effective channel estimation algorithm based on a robust cost function is proposed to mitigate impulsive noise and can provide a closed-form solution, and the application of robust estimation theory enables the proposed method to be free from localization of impulsive Noise.
Abstract: One of the major problems for accurate channel estimation in power line communication systems is impulsive noise. Traditional channel estimation algorithms are based on the assumption of Gaussian noise, or the need to locate the positions of impulsive noise. The algorithms may lose optimality when impulsive noise exists in the channel, or if the location estimation of impulsive noise is inaccurate. In the present paper, an effective channel estimation algorithm based on a robust cost function is proposed to mitigate impulsive noise. The proposed method can provide a closed-form solution, and the application of robust estimation theory enables the proposed method to be free from localization of impulsive noise and thus can guarantee that the proposed method has better performance. Simulations verified the proposed algorithm.
15 citations