DOI: 10.5937/jaes17-21031
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions.
Volume 17 article 608 pages: 284 - 294
Blind image deconvolution is an ill-posed problem that attempts to restore an acquired image degraded by unknown PSF. A variational BID implementation, called NAS-RIF, is known for being robust but prone to poor convergence under low SNR and unrealistic support. Motivated by simple yet efficient fidelity metric, this paper presents an improved NAS-RIF by reducing adverse effect of inverse high-pass filter and computationally intensive pre-deterministic noise removal, by adaptively incorporating anisotropic structural property within local neighborhood seamlessly in NAS-RIF cost function. With an automatic support region estimation, the entire deconvolution process was fully automatic. The experimental results reported herein indicated that the enhanced structural adaptive anisotropic NAS-RIF had better convergence condition,while maintaining the underlying image fidelity.
The authors would like to thank various public DICOM repositories, e.g., www.dicomlibrary.com/, www.aycan.de/, and the referenced url to imaging database therein for images used in the above experiments. This study was partly supported by SUT-OROG grant.
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