A Novel Speckle Noise Reduction Algorithm for Old Movies Recovery

2018 ◽  
Author(s):  
Chen Liu ◽  
Xiaoguang Li ◽  
Li Zhuo ◽  
Jiafeng Li ◽  
Qingfeng Zhou
Keyword(s):  
Noise Reduction ◽  
Speckle Noise ◽  
Reduction Algorithm ◽  
Speckle Noise Reduction ◽  
Noise Reduction Algorithm

Speckle Noise Reduction Algorithm Based on Principle of Shearing Interferometry

2011 ◽  
Vol 38 (7) ◽  
pp. 0708003
Author(s):  
钱晓凡 Qian Xiaofan ◽  
饶帆 Rao Fan ◽  
林超 Lin Chao ◽  
李斌 Li Bin
Keyword(s):  
Noise Reduction ◽  
Speckle Noise ◽  
Reduction Algorithm ◽  
Shearing Interferometry ◽  
Speckle Noise Reduction ◽  
Noise Reduction Algorithm

Wavelet Denoising of SAR Images Corrupted by Speckle Noise Using Cycle Spinning

2013 ◽  
Vol 325-326 ◽  
pp. 1584-1587
Author(s):  
Ming Wei Ji ◽  
Yan Li Liu ◽  
De Xiang Zhang
Keyword(s):  
Noise Reduction ◽  
Speckle Noise ◽  
Speckle Reduction ◽  
Sar Images ◽  
Unknown Variance ◽  
Reduction Techniques ◽  
Cycle Spinning ◽  
Gibbs Phenomena ◽  
Speckle Noise Reduction ◽  
Noise Reduction Algorithm

A novel and efficient speckle noise reduction algorithm based on wavelet transform by cycle spinning for removing speckle of unknown variance and minimizing the effect of pseudo-Gibbs phenomena from Synthetic Aperture Radar (SAR) images is proposed. Therefore, we show that the sub-band decompositions of logarithmically transformed SAR images. Then, we process and reconstruct multi-resolution wavelet coefficients by wavelet-threshold using cycle spinning, a technique estimating the true images as the linear average of individual estimates derived from wavelet thresholded translated versions of the noise images. Experimental results show that the proposed de-noising algorithm is possible to achieve an excellent balance between suppresses speckle effectively and weaken as many image Gibbs phenomena as possible. Quantitative and qualitative comparisons of the results obtained by the new method with the results achieved from the other speckle noise reduction techniques demonstrate its higher performance for speckle reduction in SAR images.

scholarly journals Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 319
Author(s):  
Chan-Rok Park ◽  
Seong-Hyeon Kang ◽  
Young-Jin Lee
Keyword(s):  
Image Quality ◽  
Noise Reduction ◽  
Total Variation ◽  
Parallel Imaging ◽  
Pulse Sequence ◽  
Reduction Algorithm ◽  
Median Filters ◽  
Reduction Techniques ◽  
Imaging Results ◽  
Noise Reduction Algorithm

Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-ACDixon-CAIPI) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-ACDixon-GRAPPA) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting 18F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-ACDixon-CAIPI PET image was better than that of the MR-ACDixon-GRAPPA PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.

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