A Blind Blur Detection Method for Electro-optic (EO) Images

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Published Sep 24, 2018
Greg Bower

Abstract

Blurring in Electro-Optic (EO) images is a significant issue that can arise due to the payload and platform operations.  It would be advantageous for unmanned platforms to determine if significant blurring is present within captured images before the images are observed and the collection sequence has ended.  In this way, the degradation can be identified and remedied in operation in real-time.  In this paper, we demonstrate that a statistical algorithm called Symbolic Analysis (SA) is suitable for detecting blurring in the output images of EO systems.  The SA algorithm adapted from previous work is described and demonstrated on an example image with artificial Gaussian-based blurring induced.

How to Cite

Bower, G. (2018). A Blind Blur Detection Method for Electro-optic (EO) Images. Annual Conference of the PHM Society, 10(1). https://doi.org/10.36001/phmconf.2018.v10i1.351
Abstract 218 | PDF Downloads 289

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Keywords

Blind Blur Detection, Statistics, Image Processing, Image Degradation

Section
Poster Presentations