Format

Send to

Choose Destination
See comment in PubMed Commons below
IEEE Trans Image Process. 1998;7(3):370-5. doi: 10.1109/83.661187.

Total variation blind deconvolution.

Author information

1
Dept. of Math., California Univ., Los Angeles, CA 90095-1555, USA. chan@math.ucla.edu

Abstract

In this paper, we present a blind deconvolution algorithm based on the total variational (TV) minimization method proposed. The motivation for regularizing with the TV norm is that it is extremely effective for recovering edges of images as well as some blurring functions, e.g., motion blur and out-of-focus blur. An alternating minimization (AM)implicit iterative scheme is devised to recover the image and simultaneously identify the point spread function (psf). Numerical results indicate that the iterative scheme is quite robust, converges very fast (especially for discontinuous blur), and both the image and the psf can be recovered under the presence of high noise level. Finally, we remark that psf's without sharp edges, e.g., Gaussian blur, can also be identified through the TV approach.

PMID:
18276257
DOI:
10.1109/83.661187
PubMed Commons home

PubMed Commons

0 comments

    Supplemental Content

    Full text links

    Icon for IEEE Engineering in Medicine and Biology Society
    Loading ...
    Support Center