Novel Adaptive Filter (NAF) for Impulse Noise Suppression from Digital Images

Hanji, Geeta; Latte, Mrityunjaya V.

doi:10.5121/ijbb.2014.4401

Cited by 2 publications

(5 citation statements)

References 17 publications

(16 reference statements)

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“…It has been observed that the window sizes needed for 10% to 90% noise density range between 3 to 9. Table 2 shows the better performance of the proposed NAF over the filter schemes described in [12], [17], [18] and [22] for low to high noise density cases.…”

Section: Resultsmentioning

confidence: 99%

“…A Novel Median Filter (NMF) presented in [22] addresses the task of impulsive noise cleaning from the noisy grey scale images and aims at effectively suppressing the impulse noise while preserving the edge information intact. Proposed scheme is simple and yields better denoising performance with better detail preserving up to 60-70% noise densities, but fails to perform well at higher noise situations.…”

Section: Introductionmentioning

confidence: 99%

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2014

IJBB

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In general, it is known that an adaptive filter adjusts its parameters iteratively such as size of the working window, decision threshold values used in two stage detection-estimation based switching filters, number of iterations etc. It is also known that nonlinear filters such as median filters and its several variants are popularly known for their ability in dealing with the unknown circumstances. In this paper an efficient and simple adaptive nonlinear filtering scheme is presented to eliminate the impulse noise from the digital images with an impulsive noise detection and reduction scheme based on adaptive nonlinear filter techniques. The proposed scheme employs image statistics based dynamically varying working window and an adaptive threshold for noise detection with a Noise Exclusive Median (NEM) based restoration. The intensity value of the Noise Exclusive Median (NEM) is derived from the processed pixels in local neighborhood of a dynamically adaptive window. In the proposed scheme use of an adaptive threshold value derived from the noisy image statistics returns more precise results for the noisy pixel detection. The proposed scheme is simple and can be implemented as either a single pass or a multi-pass with a maximum of three iterations with a simple stopping criterion. The goodness of the proposed scheme is evaluated with respect to the qualitative and quantitative measures obtained by MATLAB simulations with standard images added with impulsive noise of varying densities. From the comparative analysis it is evident that the proposed scheme out performs the state-of-art schemes, preferably in cases of high-density impulse noise.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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2014

IJBB

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“…Most commonly used vector filters for noise removal in color images are the Vector Directional filter (VDF) [24] and the Directional Distance Filter (DDF) [25], Vector Median Filter (VMF) and those reported in [26], [27], [28] and [29]. It is also observed that the use of fixed value of threshold is not the ultimate solution for denoising of different types of images and ideally it should be changed adaptively according to the contents of the filtering window [9], [15], [16], and [18]. In this paper, we present an impulse detection method where the decision threshold is dynamic and adaptively changes on the basis of pixel statistics within the filtering window.…”

Section: Introductionmentioning

confidence: 99%

“…Filtering of only noisy pixels results into better preservation of detail features. Most of the impulse detection methods available in the literature require a decision threshold value [16], [17] and [21] to make an intelligent decision whether the pixel under consideration is noisy or not.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to this greater weight assigned for closer pixels and lesser weights for far pixels intensity values. To overcome the above problem of complexity, new replacement techniques have been implemented instead of conventional median value replacement for corrupted pixel [15], [16], [17], [18].These approaches exploit the neighborhood pixels information for replacement unlike AMF and other filters which uses only median value. Specifically at the higher level noise density, there are situations that the median value itself might be noisy value even after applying filtering.…”

Section: Introductionmentioning

confidence: 99%

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A novel adaptive tolerance filter for random valued impulse noise suppression in digital grey and color images

Hanji

Latte²

2015

JACST

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During acquisition, transmission, storage and retrieval, quite often digital images become noised and mask the important details of an image and also present themselves with an ugly look. Such images if not processed properly, become useless for subsequent image processing operations like segmentation, classification etc. Hence the quality improvement (through denoising) of such noisy images becomes an important operation in the field of image processing. This paper proposes a two stage detection-estimation based filtering system to suppress random valued impulse noise from digital grey and color images based on neighborhood statistics of pixels of the working window under consideration. An adaptive working window and the adaptive tolerance computed from the pixels belonging to the current filtering window facilitates an appropriate detection of noisy pixels in the first phase, followed by the simple and computationally efficient restoration strategy in the second stage. The Simulation results prove that the proposed scheme exhibits much superior performance in comparison with other state of art image filtering methods in suppressing the random valued impulse noise from the digital grey and color images.

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Novel Adaptive Filter (NAF) for Impulse Noise Suppression from Digital Images

Abstract: In general, it is known that an adaptive filter adjusts its parameters iteratively Peak-Signal-to-Noise Ratio (PSNR)

Cited by 2 publications

References 17 publications

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A novel adaptive tolerance filter for random valued impulse noise suppression in digital grey and color images

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