In this paper, an evaluation technique based on several image feature attributes along with image classifications is investigated. Furthermore, a semi-supervised technique based on support vector machine (SVM) for image classification and a Locality Sensitive Hashing (LSH) based searching algorithm to search for similarity of satellite imagery is presented. Given a query image, the goal is to retrieve matching images in the database based on the shape features extracted from satellite imagery data. The experimental results demonstrate superior results based on shape features which provide a better classification accuracy using both support vector machine and the semi-supervised hashing search methods.1 2
Satellite imagery retrieval: Features & metrics evaluation
2012-03-01
1376014 byte
Conference paper
Electronic Resource
English
Simulation Of Satellite Imagery From Aerial Imagery
NTRS | 1988
|Automatic Registration of Satellite Imagery
British Library Conference Proceedings | 1998
|High Resolution Satellite Imagery Simulation
NTIS | 1987
|