Multispectral’s Three-Dimensional Model Based on SIFT Feature Extraction

Abstract

Recently, multispectral images can be captured not only from satellite sensors but also from cameras. Hence, using the photogrammetric approach, multispectral images can be manipulated to generate a three-dimensional model. The main issues regarding multispectral images were the low visibilities of the image features. Moreover, the tie point extractions on multispectral images were still in doubt. Hence, this paper examines the capabilities of the SIFT algorithm to extract feature points from multispectral images and generate the point cloud from the extracted feature points. This study chose a pothole as the subject of this research. The red, red edge, green, and near-infrared bands from the Parrot Sequoia camera were used to generate the pothole model. All captured images were processed using structure-from-motion (SfM) with Multi-View Stereo (MVS) technique. This study records the feature points extraction result and analysis of the pothole model and discuss it in this paper.