Title :
Frame representations for texture segmentation
Author :
Laine, Andrew ; Fan, Jian
Author_Institution :
Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA
fDate :
5/1/1996 12:00:00 AM
Abstract :
We introduce a novel method of feature extraction for texture segmentation that relies on multichannel wavelet frames and 2-D envelope detection. We describe and compare two algorithms for envelope detection based on (1) the Hilbert transform and (2) zero crossings. We present criteria for filter selection and discuss quantitatively their effect on feature extraction. The performance of our method is demonstrated experimentally on samples of both natural and synthetic textures
Keywords :
Hilbert transforms; feature extraction; filtering theory; image representation; image segmentation; image texture; wavelet transforms; 2D envelope detection; Hilbert transform; algorithms; feature extraction; filter selection; frame representations; multichannel wavelet frames; natural textures; performance; synthetic textures; texture segmentation; zero crossings; Calendars; Degradation; Filtering; Filters; Gaussian noise; Image restoration; Image segmentation; Pollution measurement; Signal restoration; Signal to noise ratio;
Journal_Title :
Image Processing, IEEE Transactions on
