User Manual - pancroma

78. Tutorial – Improving Image Quality with Regression________________________________________________________________PANCROMA TM has utilities for conducting multiple linear regression on satelliteband files. Such linear regressions can have many uses. One of the mostinteresting is to conduct image transformations in order to improve the colortones of processed images. The transformation equations used to approximatenatural color composites from ASTER and SPOT multispectral composite imagesare one example. The equation coefficients for these transformations weredetermined by processing a large number of images and optimizing thecoefficients for the general case. As a result, the transformations usuallyproduce acceptable results for most cases but rarely yield ideal results for aparticular case.The procedure outlined in this article is designed to create image-specifictransformation equations using multiple linear regression to compute thecoefficients. The main advantage of this approach is that the transformationequation is optimized for the particular target image of interest, and can oftenyield improved results over a general transformation equation.The objective of this example will be to improve the color tones of a pansharpened image produced by the HSI pan sharpening process. However thetechnique outlined can be used to create a transformation equation for anyimage, as long as a suitable reference image is available, as will be shownbelow.As discussed in previous articles and in the PANCROMA TM Instruction Manual,pan sharpening Landsat multispectral band files using the Landsat panchromaticband can create spectral distortions. This is a result of the characteristics of theLandsat panchromatic sensor. Rather than being sensitive to the visiblespectrum, its sensitivity is shifted to longer wavelength electromagnetic radiation,so that it excludes the blue band and includes the near infrared (NIR) band. As aresult, pan sharpening with the Landsat panchromatic band yields an image thatcan show unnatural color tones. One remedy is to use the near infrared band tocorrect the panchromatic band. The PANCROMA TM AJISANE and XIONGalgorithms do this. Another possible approach is to create a transformationequation that can be used to post-process the image to correct spectraldistortions. This is the technique that will be demonstrated in this article. Theprocedure to create the transformation will be as follows:• Create a pan sharpened image using the HSI process• Decompose the pan sharpened RGB image into its component blue,green and red band files• Resize these band files to match the row and column counts of the originalsource band files376