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.

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 AN FPGA IMPLEMENTATION OF MODIFIED DECISION BASED UNSYMMETRICAL TRIMMED MEDIAN FILTER FOR THE REMOVAL OF SALT AND PEPPER NOISE IN DIGITAL IMAGES

2014 ◽  
pp. 159-164
Author(s):  
CHAITANYA BETHINA ◽  
M. PREMKUMAR
Keyword(s):  
Noise Suppression ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Noise Removal ◽  
Mean Value ◽  
Low Noise ◽  
Color Images ◽  
Salt And Pepper Noise ◽  
Noisy Pixel ◽  
Salt And Pepper

A modified decision based unsymmetrical trimmed median filter algorithm for the restoration of gray scale, and color images that are highly corrupted by salt and pepper noise is proposed in this paper. Images are often corrupted by impulse noise during acquisition and transmission; thus, an efficient noise suppression technique is required before subsequent image processing operations. Median filter (MF) is widely used in noise removal methods due to its denoising capability and computational efficiency. However, it is effective only for low noise densities. Extensive experimental results demonstrate that our method can obtain better performances in terms of both subjective and objective evaluations than denoising techniques. Especially, the proposed method can preserve edges very well while removing salt and pepper noise. Modified Decision Based Algorithm (MDBA), and Progressive Switched Median Filter (PSMF) shows better results at low and medium noise densities. At high noise densities, their performance is poor. A new algorithm to remove high-density salt and pepper noise using modified Decision Based Unsymmetric Trimmed Median Filter (DBUTMF) is proposed. The proposed algorithm replaces the noisy pixel by trimmed median. Since our algorithm is algorithmically simple, it is very suitable to be applied to many real-time applications and higher noise densities. When all the pixel values are 0’s and 255’s then the noise pixel is replaced by mean value of all the elements present in the selected window. The proposed algorithm is tested against different grayscale and color images and it gives better Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF).

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