Conditional Expressions for Blind Deconvolution: Derivative form

2006/09/30 by S. Aogaki, Aogaki, S., I. Moritani +9
Computer Science · Engineering · #Advanced Image Processing Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Processing Techniques and Applications #Image and Signal Denoising Methods #cs.CV

paper · pdf · doi:10.48550/arxiv.cs/0610002

5 page, 3 figures, conference

arxiv created 2006/09/30 · openalex publication_date 2006/09/30 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We developed novel conditional expressions (CEs) for Lane and Bates' blind deconvolution. The CEs are given in term of the derivatives of the zero-values of the z-transform of given images. The CEs make it possible to automatically detect multiple blur convolved in the given images all at once without performing any analysis of the zero-sheets of the given images. We illustrate the multiple blur-detection by the CEs for a model image

Citations

• Conditional Expressions for Blind Deconvolution: Multi-point form

Cited by

• Simple method to eliminate blur based on Lane and Bates algorithm

Related

• Conditional Expressions for Blind Deconvolution: Multi-point form
• A Clearer Picture of Blind Deconvolution
• Kernel Diffusion: An Alternate Approach to Blind Deconvolution
• Simple method to eliminate blur based on Lane and Bates algorithm
• ECALL: Expectation-calibrated learning for unsupervised blind deconvolution