Thus far we have thought of visual/infrared and polarimetric SAR images as three-dimensional arrays of pixel intensities (columns × rows × bands) representing, more or less directly, measured radiances. In the present chapter we consider other, more abstract representations which are useful in image interpretation and analysis and which will play an important role in later chapters.

The discrete Fourier and wavelet transforms that we treat in Sections 3.1 and 3.2 convert the pixel values in a given spectral band to linear combinations of orthogonal functions of spatial frequency and distance. They may therefore be classified as spatial transformations. The principal components, minimum noise fraction and maximum autocorrelation ...

Get Image Analysis, Classification and Change Detection in Remote Sensing, 4th Edition now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.