A novel algorithm for removal of salt and pepper noise using continued fractions interpolation

Tian, Bangsen; Tan, Jieqing; Hu, Min; Wang, Yan

doi:10.1016/j.sigpro.2014.03.023

Cited by 38 publications

(26 citation statements)

References 20 publications

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“…We implement our method to comparing with the conventional methods: (MF) (Bovik, 2005), (AMF) (Gonzalez and Woods, 2006), FSBMMF (Vijaykumar et al, 2014), CFIF (Bai et al, 2014) and (Chang et al, 2007;Cumpim et al, 2016). The MATLAB software is applied in order to implement every method.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…In the next stage, the median or mean value based on the number of the uncorrupted pixels of sub-window will replace the noisy pixel. The last method is the Continued Fractions Interpolation Filter (CFIF) (Bai et al, 2014), this technique is classified as the non-median-base filter group. It applies the continued fractions interpolation method in order to calculate the new pixel value of the corrupted pixel after the noise detection step.…”

Section: Introductionmentioning

confidence: 99%

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High Density Salt and Pepper Noise Filter based on Shepard Interpolation Method

Cumpim

Punchalard

2017

Journal of Computer Science

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This paper has proposed the technique in order to remove saltand-pepper noise from the corrupted image. The proposed scheme consists of two steps. The first, the adaptive median filter is applied to noisy image for detecting noisy and noise-free pixels. Finally, the output image of previous step will be divided into many non-overlapping windows of which the noise-free pixel values are used to compute the new pixel value by the Shepard method. The experiment results of our approach had shown the better performance than the existing method.

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Section: Experiments and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High Density Salt and Pepper Noise Filter based on Shepard Interpolation Method

Cumpim

Punchalard

2017

Journal of Computer Science

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“…Our approach was based on the observation that the texture details of repaired images by most image inpainting algorithms were not prominent. Inspired by the applications of continued fractions in image processing [11,[18][19][20], we proposed a novel image inpainting algorithm by using continued fractions rational interpolation. In order to obtain better repaired results, Thiele's rational interpolation was combined with Newton-Thiele's rational interpolation to repair damaged images.…”

Section: Discussionmentioning

confidence: 99%

“…Considering that the reconstruction images have better visual effect and prominent texture by the continued fractions [11,[18][19][20], in this paper, we propose an adaptive image inpainting method based on continued fractions.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Image Inpainting Method Based on Continued Fractions Interpolation

Xing

Xia

et al. 2018

Discrete Dynamics in Nature and Society

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In view of the drawback of most image inpainting algorithms by which texture was not prominent, an adaptive inpainting algorithm based on continued fractions was proposed in this paper. In order to restore every damaged point, the information of known pixel points around the damaged point was used to interpolate the intensity of the damaged point. The proposed method included two steps; firstly, Thiele's rational interpolation combined with the mask image was used to interpolate adaptively the intensities of damaged points to get an initial repaired image, and then Newton-Thiele's rational interpolation was used to refine the initial repaired image to get a final result. In order to show the superiority of the proposed algorithm, plenty of experiments were tested on damaged images. Subjective evaluation and objective evaluation were used to evaluate the quality of repaired images, and the objective evaluation was comparison of Peak Signal to Noise Ratios (PSNRs). The experimental results showed that the proposed algorithm had better visual effect and higher Peak Signal to Noise Ratio compared with the state-of-the-art methods.

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“…Singh and Prakash proposed modified adaptive median filters which first identify the presence of impulse noise then adaptive window filtering concept is used to filter the salt & pepper noise [13]. Bai et al [26] in 2014 proposed a continued fractions interpolation filter (CFIF), where noise free pixels are left unchanged, then, the weighted mean of four-direction continued fractions interpolation is computed to estimate the corrupted pixel value. Kayhan [27] in 2014 proposed a 2-stage impulse noise removal system where first, a neuro-fuzzy based impulse noise detector (NFIDET) is introduced to identify the noisy pixels.…”

Section: Evolution Through the Yearsmentioning

confidence: 99%