Processing of images based on blind evaluation of noise type and characteristics

Vladimir V. Lukin; Sergey K. Abramov; Nikolay N. Ponomarenko; Mikhail L. Uss; Benoit Vozel; Kacem Chehdi; Jaakko T. Astola

doi:10.1117/12.830058

28 September 2009 Processing of images based on blind evaluation of noise type and characteristics

Vladimir V. Lukin, Sergey K. Abramov, Nikolay N. Ponomarenko, Mikhail L. Uss, Benoit Vozel, Kacem Chehdi, Jaakko T. Astola

Author Affiliations +

Proceedings Volume 7477, Image and Signal Processing for Remote Sensing XV; 74770B (2009) https://doi.org/10.1117/12.830058
Event: SPIE Remote Sensing, 2009, Berlin, Germany

Abstract

Most modern methods of image processing exploit a priori knowledge or estimates of noise type and its characteristics obtained in blind or interactive manner. However, the results of noise type blind determination can be false with some hopefully rather small probability. Similarly, the obtained estimates of noise parameters are characterized by certain accuracy. Clearly, false decisions and errors of estimates influence performance of image processing techniques that exploit the information on noise properties obtained in a blind manner. In this paper, we consider some aspects of such influence for several typical applications.

Citation Download Citation

Vladimir V. Lukin, Sergey K. Abramov, Nikolay N. Ponomarenko, Mikhail L. Uss, Benoit Vozel, Kacem Chehdi, and Jaakko T. Astola "Processing of images based on blind evaluation of noise type and characteristics", Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74770B (28 September 2009); https://doi.org/10.1117/12.830058

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