Questions tagged [blind-deconvolution]

is a set of methods aimed to solve the problem of recovering (reconstructing) precise version of a distorted (transformed) signal, where the distortion (transform) matrix (kernel) or the Point Spread Function (PSF) is unknown.

Filter by
Sorted by
Tagged with
11
votes
1answer
227 views

Quantitative Comparison of Scaled, Delayed and Warped Signals

The following question is detailed in 1D, with time as the ordinal variable. Similar questions could apply in other dimensions. In several signal processing techniques, such as blind source ...
3
votes
1answer
317 views

Why Sparse Priors Like Total Variation Opts to Concentrate Derivatives at a Small Number of Pixels?

When performing image deconvolution (deblurring), people often make use of priors to get rid of the illness of the problem. One very common prior is total variation, a sparse prior. Compared to ...
4
votes
1answer
2k views

Constant Modulus Algorithm and the Gradient Operation

CMA is a blind channel equalization algorithm with the details presented above. I am facing 3 difficulties and shall appreciate help Q1: Does $H$ and the bar over $\bar{y_k}$ represent the Transpose ...