Adaptive Noise Reduction Scheme for Salt and Pepper

Gebreyohannes, Tina

doi:10.5121/sipij.2011.2405

Cited by 10 publications

(13 citation statements)

References 9 publications

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“…1 [17] where {Y 1 , Y 2 , Y 4 } belongs to Y Z1 , which are in the upper left portion of the mask. The processed value of Y K1 is calculated as follows:…”

Section: Stage 3: Directional Filteringmentioning

confidence: 99%

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Directional multi-pass median filter for impulse noise reduction

Vajpai

Mehta²

2013

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)

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A novel two-stage directional multi-pass median filter (DMPMF) for reducing impulse noise has been proposed in this paper. It is a progressive technique wherein for each pass, median is substituted for each noisy pixel even if one noise free pixel exists in its surrounding 3x3 window otherwise the pixel is kept intact. The initial pass replaces only a fraction of the total number of noise-corrupted pixels in the corrupted image. With increasing number of passes, the number of pixels covered increases, and after a few passes, all or most of the noisy pixels are covered. Each pass gradually improves the quality of the restored image. Thereafter, directional filtering is applied to restore the fine details of the final image. The efficacy of the proposed algorithm is determined by applying it to different images. It produces better results in terms of the qualitative and quantitative measures of the image for both low and high density noise in comparison to many existing techniques.

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“…1 [17] where {Y 1 , Y 2 , Y 4 } belongs to Y Z1 , which are in the upper left portion of the mask. The processed value of Y K1 is calculated as follows:…”

Section: Stage 3: Directional Filteringmentioning

confidence: 99%

“…Each pass gradually improves the quality of the restored image. Thereafter, directional filtering [17] is applied to preserve the details and edges of the restored image. Computational simulation indicates that DMPMF surpasses many other well established techniques [10]- [16] in terms of PSNR.…”

Section: Introductionmentioning

confidence: 99%

Directional multi-pass median filter for impulse noise reduction

Vajpai

Mehta²

2013

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)

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“…Improving the quality of the image (Image Enhancement) is an interesting thing with the challenges inherent in image processing, this also applies to the contrast enhancement or image quality improvement [1]. Some of the images may decrease the quality to be darker even damaged can be caused by noise or because of damage to the recording device cause the object in the image becomes unclear, making it difficult to be processed again [2] [3].…”

Section: Introductionmentioning

confidence: 99%

Image Qualiy Improvement Using Algorithm Spatial Median Filter And Adaptive Fuzzy Contrast Enhacement

Marpaung¹,

Zarlis²,

Situmorang³

2019

Proceedings of the Proceedings of the 1st Workshop on Multidisciplinary and Its Applications Part 1, WMA-01 2018, 19-20 January

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This study aims to increase the image quality in terms of contrast and noise removal, it is necessary to do processing on the image in order to be interpreted in accordance with the desired. Image in question is a static grayscale images with 8-bit PNG that have low contrast and noise levels above 10% ie 15%-50% at intervals of 5%. The author uses algorithms Median Spatial Filter (SMF) to reduce noise and Fuzzy Adaptive Contrast Enhancement Algorithm With Details Serving (AFCDP) for enhancing the contrast, where the two algorithms are combined. This technique is excellent in image enhancement, where the results of tests performed combination model can improve the image of the highest quality at 15% the percentage of noise with PSNR = 26.417 and SE = 0.0387.

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“…[1]. The noise is scattered through the image in such a way that pixels can take only the minimum and maximum value (0-255) in the dynamic range; it may leads to corrupted image [2]. Many algorithms have been proposed to remove the impulse (salt and pepper) noise.…”

Section: Introductionmentioning

confidence: 99%

An efficient algorithm for removal of impulse noise in color image through efficient modified decision based unsymmetric trimmed median filter

Tondare¹,

Tekale²

2015

2015 IEEE International Advance Computing Conference (IACC)

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In the world of image processing domain, removal of high density impulse noise is always a prominent area for research. In this paper, an efficient Modified Decision based unsymmetric trimmed median filter algorithms for the removal of impulse noise has been proposed with color images rather than gray scale images by separation red-green-blue plane of color image. The performance of the system is analyzed in terms of Mean square error (MSE), Peak signal to noise ratio (PSNR) image enhancement factor (IEF) and time required for executing the algorithms for different noise densities. Simulation results shows that proposed algorithm outperforms the existing algorithms even at high noise densities for color images. Many experiments are conducted to validate efficiency of the proposed algorithm.Keywords-Image Processing, Impulse noise, Mean square error, peak signal to noise ratio, image enhancement factor.

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Adaptive Noise Reduction Scheme for Salt and Pepper

Abstract: ABSTRACT

Cited by 10 publications

References 9 publications

Directional multi-pass median filter for impulse noise reduction

Directional multi-pass median filter for impulse noise reduction

Image Qualiy Improvement Using Algorithm Spatial Median Filter And Adaptive Fuzzy Contrast Enhacement

An efficient algorithm for removal of impulse noise in color image through efficient modified decision based unsymmetric trimmed median filter

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