Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science


DOI: 10.5937/jaes17-21031
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions. 
Creative Commons License

Volume 17 article 608 pages: 284 - 294

Paramate Horkaew* 
Suranaree University of Technology, Thailand

Tanawat Kwanpak 
Suranaree University of Technology, Thailand

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.

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The authors would like to thank various public DICOM repositories, e.g.,,, 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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