Texture tone feature extraction and analysis

A new texture measurement and the Mahalanobis classifier with a generalized inverse scheme were developed to generate decision maps of terrain features with digitized B/W photographs on a pixel by pixel basis. Eight scenes within the Northeast test area, four low altitude and four high altitude, were analyzed yielding a hit-rate of about 90% with properly digitized image data. To determine the degree of non-normal behavior of the texture variables, the stable distribution models were utilized. Methods of estimating the stable parameters of the texture variables were developed. It is found that fifty % of the texture variables are not normally distributed. Since the stable distribution models are capable of incorporating the skewness parameters into the classification process, it is recommended as a new classifier for image data analysis.