A VQ-based blur identification algorithm

Ryo Nakagaki*, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

The estimation of the point spread function (PSF) of the degradation system is often a necessary first step in the restoration of blurred images. In this work, a novel Vector Quantization (VQ)-based blur identification algorithm is presented. A number of codebooks are designed corresponding to various versions of the blurring function. Prototype images blurred by each candidate blur are used. Only the non-flat regions for specific frequency bands are represented by the entries of the codebooks. Given a noisy and blurred image, one of the codebooks is chosen based on a similarity measure, therefore providing the identification of the blur. Simulations are performed for various blurring functions and noise levels. The results demonstrate the effectiveness of the proposed algorithms.

Original languageEnglish (US)
Pages (from-to)725-728
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
StatePublished - 2003
Event2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong
Duration: Apr 6 2003Apr 10 2003

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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