Subpixel level mapping of remotely sensed image using colorimetry

The problem of extracting proportion of classes present within a pixel has been a challenge for researchers for which already numerous methodologies have been developed but still saturation is far ahead, since still the methods accounting these mixed classes are not perfect and they would never be perfect until one can talk about one to one correspondence for each pixel and ground data, which is practically impossible. In this paper a step towards generation of new method for finding out mixed class proportions in a pixel on the basis of the mixing property of colors as per colorimetry. The methodology involves locating the class color of a mixed pixel on chromaticity diagram and then using contextual information mainly the location of neighboring pixels on chromaticity diagram to estimate the proportion of classes in the mixed pixel. Also the resampling method would be more accurate when accounting for sharp and exact boundaries. With the usage of contextual information can generate the resampled image containing only the colors which really exist. The process is simply accounting the fraction and then the number of pixels by multiplying the fraction by total number of pixels into which one pixel is splitted to get number of pixels of each color based on contextual information. (C) 2017 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V.