Reduction of speckle noise from medical images using principal component analysis image fusion

2014 ◽  
Author(s):  
Indrajeet Kumar ◽  
H.S Bhadauria ◽  
Jitendra Virmani ◽  
Jyoti Rawat
Keyword(s):  
Principal Component Analysis ◽  
Image Fusion ◽  
Medical Images ◽  
Principal Component ◽  
Speckle Noise ◽  
Component Analysis

Laser Active Image-Denoising Based on Principal Component Analysis with Local Pixel Grouping

2014 ◽  
Vol 571-572 ◽  
pp. 753-756
Author(s):  
Wei Li Li ◽  
Xiao Qing Yin ◽  
Bin Wang ◽  
Mao Jun Zhang ◽  
Ke Tan
Keyword(s):  
Principal Component Analysis ◽  
Image Denoising ◽  
Principal Component ◽  
Speckle Noise ◽  
Component Analysis ◽  
Median Filtering ◽  
Denoising Method ◽  
Structure Information ◽  
Pixel Grouping ◽  
Low Dimensional

Denoising is an important issue for laser active image. This paper attempted to process laser active image in the low-dimensional sub-space. We adopted the principal component analysis with local pixel grouping (LPG-PCA) denoising method proposed by Zhang [1], and compared it with the conventional denoising method for laser active image, such as wavelet filtering, wavelet soft threshold filtering and median filtering. Experimental results show that the image denoised by LPG-PCA has higher BIQI value than other images, most of the speckle noise can be reduced and the detail structure information is well preserved. The low-dimensional sub-space idea is a new direction for laser active image denoising.

scholarly journals Terahertz / Visible Dual-band Image Fusion Based on Hybrid Principal Component Analysis

2019 ◽  
Vol 1187 (4) ◽  
pp. 042096 ◽  
Author(s):  
Yuanmeng Zhao ◽  
Yulong Qiao ◽  
Cunlin Zhang ◽  
Yuejin Zhao ◽  
Hong Wu
Keyword(s):  
Principal Component Analysis ◽  
Image Fusion ◽  
Principal Component ◽  
Component Analysis ◽  
Dual Band ◽  
Band Image
Sign in / Sign up

Export Citation Format

Share Document