A GPU Parallel Algorithm for Image Denoising Based on Wavelet Transform Coefficients Thresholding

2018 ◽  
Author(s):  
Ardelio Galletti ◽  
Livia Marcellino ◽  
Luigi Russo
Keyword(s):  
Wavelet Transform ◽  
Parallel Algorithm ◽  
Image Denoising ◽  
Transform Coefficients

scholarly journals An Image Denoising Method with Enhancement of the Directional Features Based on Wavelet and SVD Transforms

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Min Wang ◽  
Zhen Li ◽  
Xiangjun Duan ◽  
Wei Li
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Image Denoising ◽  
High Frequency ◽  
Low Frequency ◽  
Singular Value ◽  
Denoising Method ◽  
Diagonal Part ◽  
Value Decomposition ◽  
Image Part

This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD), with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts), with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with image rotations and the enhancement of the directional features: to filter the diagonal part, one needs first to rotate it 45 degrees and rotate it back after filtering. Finally, reconstruct the image from the low-frequency part and the filtered high-frequency parts by the inverse wavelet transform to get the final denoising image. Experiments show the effectiveness of this method, compared with relevant methods.

Study on Damage Detection of Bridge Based on Wavelet Multi-Scale Analysis

2013 ◽  
Vol 639-640 ◽  
pp. 1010-1014 ◽  
Author(s):  
Ke Ding ◽  
Ting Peng Chen
Keyword(s):  
Wavelet Transform ◽  
Damage Detection ◽  
Detection Method ◽  
Mode Shapes ◽  
Scale Analysis ◽  
Multi Scale ◽  
Damage Location ◽  
Transform Coefficients ◽  
Beam Bridge ◽  
Multi Scale Analysis

The damage detection method based on wavelet multi-scale analysis is presented in the paper. The damage location can be identified by analyzing the multi-scale wavelet transform coefficients of curvatures of mode shapes. The extreme value of wavelet transform coefficients indicates the damage location. But it is difficult to detect the location of defect if the defect is near to the equilibrium position of vibration. In order to solve this problem, we put forward a method which is to add the wavelet transform coefficients of multi modals together. The method can effectively overcome the above problem. Three damage situations of simply supported beam bridge are discussed in the paper. The results show that the peaks of wavelet transform coefficients indicate the damage location of structural. It is possible to pinpoint the damage location based on wavelet multi-scale analysis on curvatures of mode shapes.

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