scholarly journals Multiscale Tensor Dictionary Learning Approach for Multispectral Image Denoising

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 51898-51910 ◽  
Author(s):  
Lin Zhai ◽  
Yanbo Zhang ◽  
Hongli Lv ◽  
Shujun Fu ◽  
Hengyong Yu
Keyword(s):  
Image Denoising ◽  
Dictionary Learning ◽  
Multispectral Image ◽  
Learning Approach

Clustering-based natural image denoising using dictionary learning approach in wavelet domain

2018 ◽  
Vol 23 (17) ◽  
pp. 8013-8027 ◽  
Author(s):  
Asem Khmag ◽  
Abd Rahman Ramli ◽  
Noraziahtulhidayu Kamarudin
Keyword(s):  
Image Denoising ◽  
Dictionary Learning ◽  
Natural Image ◽  
Learning Approach ◽  
Wavelet Domain

A method for remote sensing image denoising based on structured dictionary learning and cloud computing

2020 ◽  
pp. 002072092093107
Author(s):  
Ru Yang ◽  
Zhentao Qin ◽  
Xiangyu Zhao
Keyword(s):  
Remote Sensing ◽  
Cloud Computing ◽  
Image Denoising ◽  
Dictionary Learning ◽  
Learning Algorithm ◽  
Signal To Noise Ratio ◽  
Remote Sensing Data ◽  
Remote Sensing Image ◽  
Multispectral Image ◽  
Structured Dictionary

With the emerging technology of remote sensing, a huge amount of remote sensing data is collected and stored in the remote sensin02222g platform, and the transmission and processing of data on the platform is extremely wasteful. It is essential to incorporate the speedy remote sensing processing services in an integrated cloud computing architecture. In order to improve the denoising ability of remote sensing image, a new structured dictionary-based method for multispectral image denoising based on cluster is proposed. This method incorporates both the locality of spatial and the correlation across spectrum of multispectral image. Remote sensing image is divided into different groups by clustering, and sparse representation coefficients of spatial and spectral and dictionary is obtained according to the dictionary learning algorithm. After threshold processing, the similar blocks are averaged and realized with multispectral remote sensing image denoising. The algorithm is applied to denoise the noisy remote sensing image of Maoergai area in the upper Minjiang which contain typical vegetation and soil is chosen as study area, simulation results show that higher peak-signal to noise ratio can be obtained as compared to other recent image denoising methods.

Dictionary learning approach for image deconvolution with variance estimation

2014 ◽  
Vol 53 (25) ◽  
pp. 5677 ◽  
Author(s):  
Hang Yang ◽  
Ming Zhu ◽  
Xiaotian Wu ◽  
Zhongbo Zhang ◽  
Heyan Huang
Keyword(s):  
Dictionary Learning ◽  
Variance Estimation ◽  
Learning Approach ◽  
Image Deconvolution

Spectral Dictionary Learning Based Multispectral Image Compression

2019 ◽  
pp. 140-144
Author(s):  
Wei Liang ◽  
Yinghui Wang ◽  
Wen Hao ◽  
Xiuxiu Li ◽  
Xiuhong Yang ◽  
...  
Keyword(s):  
Image Compression ◽  
Dictionary Learning ◽  
Multispectral Image ◽  
Multispectral Image Compression
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