A New Methodology for Spectral-Spatial Classification of Hyperspectral Images

Algorithm 1

The segmentation of hyperspectral image.

(1) Perform linear contrast stretch algorithm [20] on the hyperspectral image. This

  step can ensure the grey value of each hyperspectral band is in 0–255 and

  enhance the image quality simultaneously.

(2) Generate a random number that satisfies the uniform distribution.

(3) Select the th band if , where denotes

  the cumulate density function of the distribution.

(4) Set and renormalize the distribution.

(5) Repeat Step  2 to Step  4 until three spectral bands have been selected.

(6) Apply SRM to segment the image composed by the selected three spectral bands.