Restoration of randomly sampled blurred images

Arthur Forman; Abhijit Mahalanobis

doi:10.1117/12.2220828

12 May 2016 Restoration of randomly sampled blurred images

Arthur Forman, Abhijit Mahalanobis

Proceedings Volume 9844, Automatic Target Recognition XXVI; 984402 (2016) https://doi.org/10.1117/12.2220828
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

The problem this paper addresses is to create an approximation for a source image given only a randomly selected subset of pixel samples extracted from a blurred version of the source image. This problem is different from the conventional image restoration problem, which attempts to create an approximation for the source image given all of the pixel samples available in the blurred image. Our approach finds a minimum weighted L2 norm solution for the ideal image that satisfies linear constraints given by the observed samples of the blurred image.

Citation Download Citation

Arthur Forman and Abhijit Mahalanobis "Restoration of randomly sampled blurred images", Proc. SPIE 9844, Automatic Target Recognition XXVI, 984402 (12 May 2016); https://doi.org/10.1117/12.2220828

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