Multispectral sensor fusion using the projection-slice theorem

Vahid R. Riasati; Sookwang Ro

doi:10.1117/12.604566

28 March 2005 Multispectral sensor fusion using the projection-slice theorem

Vahid R. Riasati, Sookwang Ro

Proceedings Volume 5813, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005; (2005) https://doi.org/10.1117/12.604566
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

In this paper we discuss the utilization of the Projection-Slice Theorem, PST, to reduce a data set that display each multiple spectral band representation of an image and to extract variant features from those representation. Noise is removed from each of the one-dimensional projections of the images via PST and a wavelet transform thresholding process. The extracted features emphasize differences in spectral information from the same image and are combined through synthesis via the inverse PST. This sensor fusion method facilitates the design of filters to recognize an image with characteristics similar to the relevant features from each of the bands that have been incorporated in a combined multispectral/fused image. We present our method of feature extraction, wavelet noise removal, and data synthesis.

Citation Download Citation

Vahid R. Riasati and Sookwang Ro "Multispectral sensor fusion using the projection-slice theorem", Proc. SPIE 5813, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005, (28 March 2005); https://doi.org/10.1117/12.604566

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