Block based compressive sensing algorithm using Eigen vectors for image compression

Author(s):  
Ankita Hundet ◽  
R. C. Jain ◽  
Vivek Sharma
2018 ◽  
Vol 77 (23) ◽  
pp. 30939-30968 ◽  
Author(s):  
Iiris Lüsi ◽  
Anastasia Bolotnikova ◽  
Morteza Daneshmand ◽  
Cagri Ozcinar ◽  
Gholamreza Anbarjafari

2014 ◽  
Vol 2014 ◽  
pp. 1-23 ◽  
Author(s):  
Leonid P. Yaroslavsky

Transform image processing methods are methods that work in domains of image transforms, such as Discrete Fourier, Discrete Cosine, Wavelet, and alike. They proved to be very efficient in image compression, in image restoration, in image resampling, and in geometrical transformations and can be traced back to early 1970s. The paper reviews these methods, with emphasis on their comparison and relationships, from the very first steps of transform image compression methods to adaptive and local adaptive filters for image restoration and up to “compressive sensing” methods that gained popularity in last few years. References are made to both first publications of the corresponding results and more recent and more easily available ones. The review has a tutorial character and purpose.


Author(s):  
Yaojun Wu ◽  
Xin Li ◽  
Zhizheng Zhang ◽  
Xin Jin ◽  
Zhibo Chen

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