Classification of multispectral image using SVM and gabor filter

Abstract

The present work deals with image classification in the field of remote sensing and retinal blood vessels which is a joint venture between image processing and classification techniques. The advancement in the imagery field in terms of resolution allowed the availability of very high resolution images. Therefore, new techniques and algorithms become necessary to cope with technology. In this regard, Gabor filters have been used in a variety of image processing applications. It had a distinctive effect in improving the image and increasing its clarity and quality for further processing. In this work, the effectiveness of the Gabor filter is explored. In particular, we used Gabor features in conjunction with the SVM to classify remotely sensed data and retinal blood vessels images. The simulation results on different datasets showed that our approach is promising in the field of image classification.