Multispectral and hyperspectral imaging of shallow waters and feature extraction in shallow coastal waters

Automated methods for extracting water features from multispectral and hyperspectral imagery. Automated or AI based techniques can be applied to scientifically detect subsurface bottom types and water column properties using fast computational algorithms and image processing techniques based upon synthetic channels created from multiband sensing systems. In this research a review of image analysis techniques is presented and described with the context of modern real time methods which are called artificial techniques. One basis and description of these techniques relies upon generating synthetic channels using wavelet imaging techniques in combination with multiple wavelength contrast algorithms. In this paper and presentation techniques are demonstrated using multispectral-hyperspectral mages flown over Space Coast Florida waters. The results demonstrate the value of modern image analysis approaches to examine environmental and ecologically relevant diversity indices useful for characterizing the quality of marine habitats.