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Journal ArticleDOI

Efficient Restoration Method for Images Corrupted with Impulse Noise

Zayed M. Ramadan
- 01 Aug 2012 - 
- Vol. 31, Iss: 4, pp 1397-1406
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TLDR
The experimental results for the proposed method demonstrate that it is faster and simpler than even median filtering, and it is very efficient for images corrupted with a wide range of impulse noise densities varying from 10% to 90%.
Abstract
This paper proposes a two-stage adaptive method for restoration of images corrupted with impulse noise. In the first stage, the pixels which are most likely contaminated by noise are detected based on their intensity values. In the second stage, an efficient average filtering algorithm is used to remove those noisy pixels from the image. Only pixels which are determined to be noisy in the first stage are processed in the second stage. The remaining pixels of the first stage are not processed further and are just copied to their corresponding locations in the restored image. The experimental results for the proposed method demonstrate that it is faster and simpler than even median filtering, and it is very efficient for images corrupted with a wide range of impulse noise densities varying from 10% to 90%. Because of its simplicity, high speed, and low computational complexity, the proposed method can be used in real-time digital image applications, e.g., in consumer electronic products such as digital televisions and cameras.

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Citations
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Journal ArticleDOI

Full frequency de-noising method based on wavelet decomposition and noise-type detection

TL;DR: A new framework named Full Frequency band De-noising based on Noise-type Detection (FFD-ND) is proposed, in which a noise type is detected by analyzing autocorrelation coefficients for different noise, and then noise reduction is performed both in low and high frequency band by using different thresholds forDifferent noise models.
Journal ArticleDOI

Denoising of sparse images in impulsive disturbance environment

TL;DR: This paper introduces a method to find the positions of the corrupted pixels when the noise is not of the salt and pepper form, and can be used without explicitly imposing the image sparsity in a strict sense.
Journal ArticleDOI

Reconstruction of Sparse Signals in Impulsive Disturbance Environments

TL;DR: A criterion for selection of corrupted signal samples is proposed based on the analysis of the first step of a gradient-based iterative algorithm used in the signal reconstruction, and an iterative extension of the original criterion is introduced to enhance its selection property.
Proceedings ArticleDOI

Color impulse noise removal by modified alpha trimmed median mean filter for FVIN

Pranay Yadav, +1 more
TL;DR: This method yields a better output for color impulse noise as compare to the other filters and shows better Peak Signal to Noise Ratio (PSNR) value, Mean Square Error (MSE), Root Meansquare Error (RMSE) and with better visual and human sensing.
Journal ArticleDOI

Fuzzy SVM based fuzzy adaptive filter for denoising impulse noise from color images

TL;DR: FCM clustering has been incorporated with fuzzy- support vector machine (FSVM) classifier for classification of noisy and non-noisy pixels in removal of impulse noise from color images and proposed FSVM based fuzzy adaptive filter provides better performance than some of the established state-of-art filters.
References
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Book

Digital Image Processing Using MATLAB

TL;DR: 1. Fundamentals of Image Processing, 2. Intensity Transformations and Spatial Filtering, and 3. Frequency Domain Processing.
Journal ArticleDOI

Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

TL;DR: This scheme can remove salt-and-pepper-noise with a noise level as high as 90% and show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only.
Journal ArticleDOI

Adaptive image contrast enhancement using generalizations of histogram equalization

TL;DR: A scheme for adaptive image-contrast enhancement based on a generalization of histogram equalization (HE), which can produce a range of degrees of contrast enhancement, at one extreme leaving the image unchanged, at another yielding full adaptive equalization.
Journal ArticleDOI

Progressive switching median filter for the removal of impulse noise from highly corrupted images

TL;DR: In this paper, a progressive switching median (PSM) filter is proposed to restore images corrupted by salt-pepper impulse noise, where an impulse detection algorithm is used before filtering, thus only a proportion of all the pixels will be filtered; and progressive methods are progressively applied through several iterations.
Journal ArticleDOI

Adaptive impulse detection using center-weighted median filters

TL;DR: A novel adaptive operator is devises, which forms estimates based on the differences between the current pixel and the outputs of center-weighted median (CWM) filters with varied center weights, which consistently works well in suppressing both types of impulses with different noise ratios.
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