Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python By: Morton John Canty

Author: Morton John Canty

Introducing advanced undergraduate and graduate level techniques used in the processing of multispectral and hyperspectral remote sensing imagery, Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL covers such topics as basic Fourier, wavelet, principle components, minimum noise fraction transformation, and Ortho-rectification; panchromatic sharpening; multivariate change detection; supervised and unsupervised land cover classification; hyperspectral analysis; and topographic modeling. With programming examples in IDL and applications that support ENVI, it offers many extensions, such as for data fusion, statistical change detection, clustering and supervised classification with neural networks, all available as source code.

34M	Image Analysis, Classification and Change Detection in Remote Sensing, 4th Ed - Morton John Canty.pdf
34M	total