I know about that... what I need is this? Is there any function for representing the image in sparse domain? Like DWT2 function in MATLAB.
See L1 magic and document from Rice University..Compressive sensing group
Hi you may check the following paper about compressed imaging:
"Compressed Imaging With a Separable Sensing Operator" from IEEE Xplore,
"Kronecker Compressive Sensing" from IEEE Xplore.
If you know how to do 1D Compressed sensing, you can apply that knowledege in implementing Multi-Dimensional CS according to these papers.
Hope this will help :-)
sir Gholamreza Anbarjafari,
can u help me.. I have the same querry regarding my research.
Thanks in advance.
Hello Sir,
I am working compressive sensing on an image.
I decomposed the image (256*256) using DWT and obtained the four sub bands of each 128 *128. Now I am taking the three high frequency sub bands of each (128*1)to be measured with Measurement matrix (100*128). So therefore i would get three resultant measured vectors.This is Compression.
Reconstruction:
I would use the low frequency band(128*128) and the 3 high frequency band(128*1) using OMP to reconstruct the image.
Clarifications:
How to convert the one high frequency sub band (128 *128) into one measured vectors (128*1) ?
Please correct me if my understanding is wrong.
plz help me how can i apply compressed sensing to segmented images in python
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