@mastersthesis{Salvaggio1987_0,<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Abstract = {An automated segmentation algorithm for the isolation of pseudoinvariant features was developed.  This algorithm utilizes rate-of-change information from the thresholding process previously associated with the pseudoinvariant feature normalization technique.  This algorithm was combined with the normaliztion technique and applied to the six reflective bands of the Landsat Thematic Mapper for both urban and rural imagery.  The segmentation algorithm and normalization technique were also applied to color infrared high resolution U2 imagery.  The accuracy and precision of the normalization results were evaluated.  The technique consistently produced normalization results with errors of approximately one or two reflectance units for both the rural and urban Thematic Mapper imagery as well as the visible bands of high resolution airphoto imagery.  The segmentation algorithm shows great potential for the removal of human intervention in the pseudoinvariant feature temporal image normalization process.},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Address = {Rochester, New York, United States of America},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Author = {Carl Salvaggio},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Keywords = {automated segmentation; pseudoinvariant features; landsat; thematic mapper; image normalization},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Month = {},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;School = {Rochester Institute of Technology, College of Science, Center for Imaging Science},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Title = {Automated segmentation of urban features from Landsat Thematic Mapper imagery for use in pseudoinvariant feature temporal image normalization},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Type = {M.S. Thesis},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Url = {},<BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Year = {1987}}