Statistical Analysis of speckle noise reduction techniques for echocardiographic Images

2011 ◽  
Author(s):  
Kalpana Saini ◽  
M. L. Dewal ◽  
Manojkumar Rohit ◽  
R. B. Patel ◽  
B. P. Singh
Keyword(s):  
Statistical Analysis ◽  
Noise Reduction ◽  
Speckle Noise ◽  
Reduction Techniques ◽  
Echocardiographic Images ◽  
Speckle Noise Reduction

Speckle noise reduction in echocardiographic images of aortic valve and cardiac chambers

Optik ◽  
2015 ◽  
Vol 126 (2) ◽  
pp. 153-163 ◽  
Author(s):  
Nagashettappa Biradar ◽  
M.L. Dewal ◽  
Manoj Kumar Rohit
Keyword(s):  
Aortic Valve ◽  
Noise Reduction ◽  
Speckle Noise ◽  
Echocardiographic Images ◽  
Speckle Noise Reduction

Speckle Noise Reduction in B-Mode Echocardiographic Images: A comparison

2015 ◽  
Vol 32 (6) ◽  
pp. 435-453 ◽  
Author(s):  
Nagashettappa Biradar ◽  
Mohan Lal Dewal ◽  
Manoj Kumar Rohit
Keyword(s):  
Noise Reduction ◽  
Speckle Noise ◽  
Echocardiographic Images ◽  
Speckle Noise Reduction

scholarly journals A Review on Speckle Noise Reduction Techniques

2014 ◽  
Vol 16 (3) ◽  
pp. 74-77
Author(s):  
Er. Kritika Bansal ◽  
◽  
Er. Akwinder kaur
Keyword(s):  
Noise Reduction ◽  
Speckle Noise ◽  
Reduction Techniques ◽  
Speckle Noise Reduction

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.

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