Photo Photo Photo Photo Photo Photo

Print
E-mail
Astronomy: CLASSIFICATION AND SEGMENTATION BY UNSUPERVISED K-MEANS TECHNIQUE BASED ON DECOMPOSITION OF SINGLE-BAND REMOTELY SENSED IMAGES USING WAVELET TRANSFORMATION

 

CLASSIFICATION AND SEGMENTATION BY UNSUPERVISED K-MEANS TECHNIQUE BASED ON DECOMPOSITION OF SINGLE-BAND REMOTELY SENSED IMAGES USING WAVELET TRANSFORMATION

S. M. Ali

Remote Sensing Unit- College of Science- University of Baghdad IRAQ- Baghdad- Al-Jaderyia

ABSTRACT

An adaptive unsupervised K-means classification and segmentation techniques are introduced, based on decomposition of single-band remotely sensed images, using stationary wavelet- transform. Images by our classification technique are decomposed into 4 sub-bands using two-level stationary wavelet- transform. For each image point, a 4-dimensional vector is constructed whose components represent the same location values at the 4-wavelet sub-bands. K-means unsupervised classification method is used to perform the classification process. Image segmentation, based on color or gray slicing method is also presented..

Keywords, Classification Method, Segmentation Method, Unsupervised Classification and Segmentation, K-Means Classification, Wavelet Classification Method, Band decomposition classification, Remote sense data classification and Segmentation.


alt

 

S5 Box

Login



Register

*
*
*
*
*

Fields marked with an asterisk (*) are required.