Title :
Synthetic aperture radar segmentation using wavelets and fractals
Author :
Rogers, Steven K. ; Ruck, Dennis W. ; Tarr, Gregory L. ; Kabrisky, Matthew ; Brickey, Joseph L. ; Meer, David E. ; Homme, Albert P L ; Smiley, Steven ; Hazlett, Michael ; Willey, Kevin J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Air Force Inst. of Technol., Wright-Patterson AFB, OH, USA
Abstract :
It is shown that fractal dimension estimates and Gabor wavelet coefficients are valid features of segmenting high-resolution polarimetric synthetic aperture radar imagery. Results of training a radial basis function neural network using fractal dimension features, Gabor wavelet coefficients, and a combination of both fractal and Gabor wavelet features are presented. Current research into combining these two techniques both theoretically and empirically is presented. One-foot resolution polarimetric synthetic aperture radar imagery is successfully segmented into culture, tree, field, and shadow regions.<>
Keywords :
fractals; neural nets; picture processing; radar systems; SAR segmentation; culture region; field region; fractal dimension estimates; high resolution imagery; image segmentation; polarimetric synthetic aperture radar; radial basis function neural network; shadow regions; training; tree region; Fractals; Image processing; Neural networks; Radar;
Conference_Titel :
Systems Engineering, 1991., IEEE International Conference on
Conference_Location :
Dayton, OH, USA
Print_ISBN :
0-7803-0173-0
DOI :
10.1109/ICSYSE.1991.161072
