Title :
Iterative least squares approach to the mixture modeling problem
Author :
Srinivasan, Murari ; DeFries, Ruth
Author_Institution :
Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA
Abstract :
The mixture model is an attempt to accurately model the ground truth in the case of low-resolution remote-sensed imagery. The model assumes that a pixel in the image does not consist of a single class, but consists instead of the sum of fractions of various classes. The authors use an iterative least squares approach to estimate these fractions for every pixel. Results are provided on synthetic data as well as real Advanced Very High Resolution Radiometer (AVHRR) data from the African continent
Keywords :
geophysical signal processing; image resolution; iterative methods; least squares approximations; parallel algorithms; radiometry; remote sensing; AVHRR data; Advanced Very High Resolution Radiometer; African continent; ground truth; image pixel; iterative least squares; low-resolution remote-sensed imagery; mixture modeling problem; parallel algorithm; synthetic data; Continents; Educational institutions; Geography; High performance computing; Iterative algorithms; Iterative methods; Least squares approximation; Least squares methods; Physics computing; Pixel; Radiometry; Remote sensing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.480133
