Neural network method for characterizing video cameras

Shuangquan Zhou; Dazun Zhao

doi:10.1117/12.319755

19 August 1998 Neural network method for characterizing video cameras

Shuangquan Zhou, Dazun Zhao

Proceedings Volume 3561, Electronic Imaging and Multimedia Systems II; (1998) https://doi.org/10.1117/12.319755
Event: Photonics China '98, 1998, Beijing, China

Abstract

This paper presents a neural network method for characterizing color video camera. A multilayer feedforward network with the error back-propagation learning rule for training, is used as a nonlinear transformer to model a camera, which realizes a mapping from the CIELAB color space to RGB color space. With SONY video camera, D₆₅ illuminant, Pritchard Spectroradiometer, 410 JIS color charts as training data and 36 charts as testing data, results show that the mean error of training data is 2.9 and that of testing data is 4.0 in a 256³ RGB space.

Citation Download Citation

Shuangquan Zhou and Dazun Zhao "Neural network method for characterizing video cameras", Proc. SPIE 3561, Electronic Imaging and Multimedia Systems II, (19 August 1998); https://doi.org/10.1117/12.319755

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