Impulse noise removal using SVM classification based fuzzy filter from gray scale images

Roy, Amarjit; Singha, Joyeeta; Devi, Swapna; Laskar, Rabul Hussain

doi:10.1016/j.sigpro.2016.04.007

Cited by 87 publications

(40 citation statements)

References 33 publications

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“…A review of prior work carried out in the field of Image Deblurring Technique and the methodology put into practice to diminish their limitation is summarized as fol-lows: J.Singha [8] makes use of SVM based fuzzy filter employs impulse noise to eradicate from grayscale images. SVM is used for the impulse noise detection from images.…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid fuzzy and support vector machine based blur detection technique

Kaur¹,

Banga²

2018

IJET

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The main objective of our research work is to acquire good quality of an image which is blurred. Therefore, in this research our effort is to propose an advanced algorithm to improve the quality of an image by eliminate the blur in an efficient manner. In this paper, two types of blurred images (i.e., Gaussian blur and out of focus) are used. Deblurring techniques are mostly used to eradicate the blur of an image using different methods & parameters. To reimburse blur different types of methods like algorithm, filtering techniques, fuzzy based approach, support vector machine are used. Blur detection methods are used to eradicate the blur from a blurred section of an image which is caused by the out of focus blur and Gaussian blur.

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Section: Literature Reviewmentioning

confidence: 99%

Hybrid fuzzy and support vector machine based blur detection technique

Kaur¹,

Banga²

2018

IJET

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“…During the process of experiments, the impulse noises are artificially injected in these images. The performances are evaluated in terms of the visual quality, peak signal to noise ratio (PSNR), mean square error (MSE) [30] and structural similarity index (SSIM). The PSNR is measured in terms of dB.…”

Section: A Objective Analysismentioning

confidence: 99%

“…Li et al [27] has proposed s neuro-fuzzy network based impulse noise filtering for gray scale images. Some of the SVM classification based filtering approaches for removal of impulse noise have been implemented for gray as well color images [28,29,30].…”

Section: Introductionmentioning

confidence: 99%

Non-casual linear prediction based adaptive filter for removal of high density impulse noise from color images

Roy

Laskar

2017

AEU - International Journal of Electronics and Communications

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“…Roy et al [29], support vector machine (SVM) classification based Fuzzy filter (FF) was proposed for removal of impulse noise from gray scale images. When an image was affected by impulse noise, the quality of the image was distorted since the homogeneity among the pixels was broken.…”

Section: Related Workmentioning

confidence: 99%

Image Restoration in Noisy Free Images Using Fuzzy Based Median Filtering and Adaptive Particle Swarm Optimization - Richardson-Lucy Algorithm

Kumar¹,

Shukla²,

Tripathi³

2017

IJIES

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Abstract:In this paper, we have proposed adaptive methods for image restoration in which the input images are affected by noise which is removed by fuzzy based median filter (FMF). The noise removed images from the FMF is appears to be so there is a need to restore the images with high quality. To restore the images an APSO (Adaptive particle swarm optimization) based Richardson-Lucy (R-L) algorithm is utilized. By both FMF and APSO-RL methods the denoising and restoration of the image is performed efficiently. The performance of the image denoising and restoration technique is evaluated by comparing the result of proposed technique with the existing denoising filter and GA, PSO methods. The comparison result shows a high-quality denoising and restoration ratio for the noisy images than the existing methods, in terms of peak signal-to-noise ratio (PSNR) and second-derivative-like measure of enhancement (SDME).

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Impulse noise removal using SVM classification based fuzzy filter from gray scale images

Cited by 87 publications

References 33 publications

Hybrid fuzzy and support vector machine based blur detection technique

Hybrid fuzzy and support vector machine based blur detection technique

Non-casual linear prediction based adaptive filter for removal of high density impulse noise from color images

Image Restoration in Noisy Free Images Using Fuzzy Based Median Filtering and Adaptive Particle Swarm Optimization - Richardson-Lucy Algorithm

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