Object Recognition based on Template Matching and Correlation Method in Hyperspectral Images

Abstract

In past recent years, image processing of hyperspectral images have become more popular than earlier. New methods, techniques and logics are being evolved for extracting more information from a digital image, as the existing techniques of image processing and analyzing techniques are not quenching the thirst of today's demand. The research of image processing based on traditional low resolution image has already not satisfied the need for people to get more accurate information from high resolution hyperspectral images. The today's demand is, to get more information about some particular things and modify about a particular region from a digital hyperspectral image, this is particularly central to the urban plan and disaster observation. On the basis of analysis of the conventional techniques for information extracting from a digital image, a method of extraction particular object in hyperspectral image based on feature template correlation is proposed. There are three different pars in this technique: building the template, image match and template correlations, and object recognition. The methods are applied to several high-resolution example images, and vehicles as example object in the image are extracted and recognized. Those examples illuminate that the method proposed in this paper is very effective and accurate.