Title :
A fast method to determine co-occurrence texture features
Author :
Clausi, David A. ; Jernigan, M. Ed
Author_Institution :
Dept. of Geomantics Eng., Calgary Univ., Alta., Canada
fDate :
1/1/1998 12:00:00 AM
Abstract :
A critical shortcoming of determining texture features derived from grey-level co-occurrence matrices (GLCM´s) is the excessive computational burden. This paper describes the implementation of a linked-list algorithm to determine co-occurrence texture features far more efficiently. Behavior of common co-occurrence texture features across difference grey-level quantizations is investigated
Keywords :
feature extraction; geophysical signal processing; geophysical techniques; image texture; remote sensing; co-occurrence texture feature; fast method; geophysical measurement technique; grey-level co-occurrence matrices; grey-level quantization; image feature; image processing; image texture; land surface; linked-list algorithm; occurrence matrix; terrain mapping; Councils; Design engineering; Dynamic range; Focusing; Image segmentation; Pixel; Quantization; Remote sensing; Statistics; Systems engineering and theory;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
