Object-based analysis of motion blur and its removal by considering occluded boundaries

Yoo Chan Choung; Jeong-Ho Shin; Joon-Ki Paik

doi:10.1117/12.334719

28 December 1998 Object-based analysis of motion blur and its removal by considering occluded boundaries

Yoo Chan Choung, Jeong-Ho Shin, Joon-Ki Paik

Proceedings Volume 3653, Visual Communications and Image Processing '99; (1998) https://doi.org/10.1117/12.334719
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

An image frame in image sequences, in general, suffers from degradation due to spatially varying motions. In this paper, we propose a new image degradation model for space-variant motion blur and a spatially adaptive image restoration algorithm to remove such motion blur. For the proposed image degradation model, we mathematically analyze boundary effect which arises on the border of two image segments with different motions. We extend the already proposed model for a moving object in an arbitrary direction. In order to represent the point spread function (PSF) for motion blur in an arbitrary direction, we develop a method which distributes energy of samples in the PSF into the neighboring integer grids. In order to remove the above mentioned motion blur, we propose an object-based adaptive regularized image restoration algorithm. Both in synthetically and naturally motion blurred images, the proposed image restoration algorithm gives acceptable performance in removing motion blur and, as a result, in restoring important features, such as numbers and characters, which cannot be recognized in the input blurred image.

Citation Download Citation

Yoo Chan Choung, Jeong-Ho Shin, and Joon-Ki Paik "Object-based analysis of motion blur and its removal by considering occluded boundaries", Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); https://doi.org/10.1117/12.334719

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available