Blur detection using a neural network

Chong Sze Tong

doi:10.1117/12.211411

7 June 1995 Blur detection using a neural network

Chong Sze Tong

Proceedings Volume 2563, Advanced Signal Processing Algorithms; (1995) https://doi.org/10.1117/12.211411
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

Image restoration is an ill-posed inversion problem wherein an estimate of the ideal original image is to be extracted from a noisy and blurred observation. The ability to restore such a degraded digital image usually requires accurate knowledge of the blur function as well as additional information on the original image. Unfortunately, such a priori knowledge is not always accessible. This paper describes an iterative scheme for the identification of the blurring by making use of the neural network paradigm and the assumption of physical constraints on the blurring process.

Citation Download Citation

Chong Sze Tong "Blur detection using a neural network", Proc. SPIE 2563, Advanced Signal Processing Algorithms, (7 June 1995); https://doi.org/10.1117/12.211411

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