Salt and Pepper Noise Suppression for Medical Image by Using Non-local Homogenous Information

2019 ◽  
pp. 189-199
Author(s):  
Hu Liang ◽  
Shengrong Zhao
Keyword(s):  
Medical Image ◽  
Noise Suppression ◽  
Salt And Pepper Noise ◽  
Non Local ◽  
Salt And Pepper

A robust medical image watermarking against salt and pepper noise for brain MRI images

2016 ◽  
Vol 76 (7) ◽  
pp. 10313-10342 ◽  
Author(s):  
Seyed Mojtaba Mousavi ◽  
Alireza Naghsh ◽  
Azizah A. Manaf ◽  
S. A. R. Abu-Bakar
Keyword(s):  
Medical Image ◽  
Image Watermarking ◽  
Brain Mri ◽  
Salt And Pepper Noise ◽  
Medical Image Watermarking ◽  
Salt And Pepper

scholarly journals Research on Noise Reduction and Enhancement Algorithm of Girth Weld Image

2021 ◽  
Vol 12 (1) ◽  
pp. 9-21
Author(s):  
Xiang-Song Zhang ◽  
Wei-Xin Gao ◽  
Shi-Ling Zhu
Keyword(s):  
Kernel Function ◽  
Experimental Results ◽  
Gaussian Kernel ◽  
Enhancement Effect ◽  
Salt And Pepper Noise ◽  
Central Pixel ◽  
Local Mean ◽  
Non Local ◽  
Mixed Noise ◽  
Salt And Pepper

In order to eliminate the salt pepper and Gaussian mixed noise in X-ray weld image, the extreme value characteristics of salt and pepper noise are used to separate the mixed noise, and the non local mean filtering algorithm is used to denoise it. Because the smoothness of the exponential weighted kernel function is too large, it is easy to cause the image details fuzzy, so the cosine coefficient based on the function is adopted. An improved non local mean image denoising algorithm is designed by using weighted Gaussian kernel function. The experimental results show that the new algorithm reduces the noise and retains the details of the original image, and the peak signal-to-noise ratio is increased by 1.5 dB. An adaptive salt and pepper noise elimination algorithm is proposed, which can automatically adjust the filtering window to identify the noise probability. Firstly, the median filter is applied to the image, and the filtering results are compared with the pre filtering results to get the noise points. Then the weighted average of the middle three groups of data under each filtering window is used to estimate the image noise probability. Before filtering, the obvious noise points are removed by threshold method, and then the central pixel is estimated by the reciprocal square of the distance from the center pixel of the window. Finally, according to Takagi Sugeno (T-S) fuzzy rules, the output estimates of different models are fused by using noise probability. Experimental results show that the algorithm has the ability of automatic noise estimation and adaptive window adjustment. After filtering, the standard mean square deviation can be reduced by more than 20%, and the speed can be increased more than twice. In the enhancement part, a nonlinear image enhancement method is proposed, which can adjust the parameters adaptively and enhance the weld area automatically instead of the background area. The enhancement effect achieves the best personal visual effect. Compared with the traditional method, the enhancement effect is better and more in line with the needs of industrial field.

Decision-Based Marginal Diffusion for Salt-and-Pepper Noise Removal in Color Images

2020 ◽  
pp. 2150153
Author(s):  
Hongyao Deng ◽  
Xiuli Song ◽  
Huilian Fan
Keyword(s):  
Anisotropic Diffusion ◽  
Noise Suppression ◽  
Impulsive Noise ◽  
Geometric Analysis ◽  
Noise Removal ◽  
Diffusion Method ◽  
Salt And Pepper Noise ◽  
The Arts ◽  
Independent Distribution ◽  
Salt And Pepper

Salt-and-pepper noise suppression for vector-valued images usually employs vector median filtering, total variation L1 model, diffusion methods and variants. These approaches, however, often introduce excessive smoothing and can result in extensive visual feature blurring and are suitable only for images with low intensity noise. In this paper, a new method, as an important preprocessing step in cyber-physical systems, is presented to suppress salt-and-pepper noise that can overcomes this limitation. This method first detects the corrupted pixels and then restores them using channel-wise anisotropic diffusion. The means is twofold. On the one hand, the marginal approach is used to perform noise suppression separately in each channel because the contaminative pixel components are of independent distribution. On the other hand, a decision-based anisotropic diffusion method is applied to each channel to restores them. The anisotropic diffusion is an energy-dissipating process with time, and dependent on geometric analysis of shape of the energy surface. Simulation results indicate that the proposed method for impulsive noise removal achieves the state-of-the-arts results.

scholarly journals Image Recovery with Data Missing in the Presence of Salt-and-Pepper Noise

2019 ◽  
Vol 9 (7) ◽  
pp. 1426
Author(s):  
Hongqing Liu ◽  
Liming Hou ◽  
Zhen Luo ◽  
Yi Zhou ◽  
Xiaorong Jing ◽  
...  
Keyword(s):  
Noise Suppression ◽  
Impulsive Noise ◽  
Subjective Evaluation ◽  
Estimation Algorithm ◽  
Joint Estimation ◽  
Image Recovery ◽  
Salt And Pepper Noise ◽  
Degrade Image Quality ◽  
Data Missing ◽  
Salt And Pepper

In this paper, an image recovery problem under the case of salt-and-pepper noise and data missing that degrade image quality is addressed if they are not effectively handled, where the salt-and-pepper noise as the impulsive noise is remodeled as a sparse signal due to its impulsiveness and the data missing pattern, denoted by a sparse vector, contains only zeros and ones to formulate the data missing. In particular, the salt-and-pepper noise and data missing are reformatted by their sparsity, respectively. The wavelet and framelet domains are explored to sparsely represent the image in order to accurately reconstruct the clean image. From the reformulations conducted and to recover the image, under one optimization framework, a joint estimation is developed to perform the image recovery, the salt-and-pepper noise suppression, and the missing patter estimation. To solve the optimization problem, two efficient solvers are developed to obtain the joint estimation solution, and they are based on the alternating direction method of multipliers (ADMM) and accelerated proximal gradient (APG). Finally, numerical studies verify that the joint estimation algorithm outperforms the state-of-the-art approaches in terms of both objective and subjective evaluation standards.

scholarly journals Medical image security authentication method based on wavelet reconstruction and fractal dimension

2021 ◽  
Vol 17 (4) ◽  
pp. 155014772110141
Author(s):  
Tiankai Sun ◽  
Xingyuan Wang ◽  
Da Lin ◽  
Rong Bao ◽  
Daihong Jiang ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Medical Image ◽  
Multiplicative Noise ◽  
Image Authentication ◽  
Salt And Pepper Noise ◽  
Image Transformation ◽  
Security Authentication ◽  
Noise Image ◽  
Medical Image Authentication ◽  
Salt And Pepper

In this article, based on wavelet reconstruction and fractal dimension, a medical image authentication method is implemented. According to the local and global methods, the regularity of the mutation structure in the carrier information is analyzed through a measurement defined in the medical image transformation domain. To eliminate the redundancy of the reconstructed data, the fractal dimension is used to reduce the attributes of the reconstructed wavelet coefficients. According to the singularity of the fractal dimension of the block information, the key features are extracted and the fractal feature is constructed as the authentication feature of the images. The experimental results show that the authentication scheme has good robustness against attacks, such as JPEG compression, multiplicative noise, salt and pepper noise, Gaussian noise, image rotation, scaling attack, sharpening, clipping attack, median filtering, contrast enhancement, and brightness enhancement.

Salt-and-Pepper Noise Removal Based on Image Patch Reordering

2014 ◽  
Vol 701-702 ◽  
pp. 352-356
Author(s):  
Xiong Liang Wang ◽  
Chun Ling Wang
Keyword(s):  
Quantitative Assessment ◽  
Noise Suppression ◽  
Noise Removal ◽  
Experimental Results ◽  
New Method ◽  
Salt And Pepper Noise ◽  
Image Patch ◽  
Qualitative And Quantitative ◽  
Salt And Pepper

A new method based on image patch reordering for removing salt-and-pepper noise from corrupted images is presented. Firstly, the problem of salt-and-pepper noise removal can be turned into the problem of image in-painting. Then, we can use the image patch reordering method to recover the missing pixels and fulfill the salt-and-pepper noise removal. Experimental results demonstrate that the proposed method obtain much better performance in terms of both qualitative and quantitative assessment. Especially, the proposed method provides the improvement in the performance of noise suppression and detail preservation.

Sign in / Sign up

Export Citation Format

Share Document