A parameterized statistical sonar image texture model

J. Tory Cobb; K. Clint Slatton

doi:10.1117/12.777185

29 April 2008 A parameterized statistical sonar image texture model

J. Tory Cobb, K. Clint Slatton

Proceedings Volume 6953, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII; 69530K (2008) https://doi.org/10.1117/12.777185
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

Single-point statistical properties of envelope-detected data such as signal returns from synthetic aperture radar and sonar have traditionally been modeled via the Rayleigh distribution and more recently by the K-distribution. Two-dimensional correlations that occur in textured non-Gaussian imagery are more difficult to model and estimate than Gaussian textures due to the nonlinear transformations of the time series data that occur during envelope detection. In this research, textured sonar imagery is modeled by a correlated K-distribution. The correlated K-distribution is explained via the compound representation of the one-dimensional K-distribution probability density function. After demonstrating the model utility using synthetically generated imagery, model parameters are estimated from a set of textured sonar images using a nonlinear least-squares fit algorithm. Results are discussed with regard to texture segmentation applications.

Citation Download Citation

J. Tory Cobb and K. Clint Slatton "A parameterized statistical sonar image texture model", Proc. SPIE 6953, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII, 69530K (29 April 2008); https://doi.org/10.1117/12.777185

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