Image enhancement can be defined as conversion of the image quality to a better and more understandable level for feature extraction or image interpretation, while radiometric correction is to reconstruct the physically calibrated value from the observed data.

On the other hand, feature extraction can be defined as the operation to quantify the image quality through various parameters or functions, which are applied to the original image.

These processes can be considered as conversion of the image data. Image enhancement is applied mainly for image interpretation in the form of an image output, while feature extraction is normally used for automated classification or analysis in a quantitative form (see Figure 10.1.1).

a. Image Enhancement
Typical image enhancement techniques include gray scale conversion, histogram conversion, color composition, color conversion between RGB and HSI, etc., which are usually applied to the image output for image interpretation.

b. Feature Extraction
Features involved in an image are classified as follows.
(1) Spectral features
special color or tone, gradient, spectral parameter etc.
(2) Geometric features
edge, linearment, shape, size, etc.
(3) Textural features
pattern, spatial frequency, homogeneity, etc.

Figure 10.1.2 shows three examples of spectral, geometric and textural feature extraction.

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