A Review of Optical Imagery and Airborne LiDAR Data RegistrationMethods

Representing a scene completely from remote sensing data requires both spectral and 3-D-surface information. Integration of spectral information from optical images and 3-D-surface information from LiDAR is important in a number of remote sensing applications such as feature extraction, image classification, image analysis, building extraction, 3-D city modelling, canopy modelling etc. Therefore, numerous methods have been developed in the last decade to align both data sets into a common reference frame to effectively utilize their complementary characteristics. However, due to the significantly different characteristics between optical image and LiDAR data, there are a number of technical challenges in the alignment of both data sets. Different research papers introduced different strategy or methodology to overcome the challenges, reaching different alignment/registration results. This paper presents a review of classical and up to date optical-LiDAR registration methods with the emphasis on control point detection and matching. The aim of this paper is to provide readers with an overview of existing methods, identify their advantages and limitations, and give readers the overall information on what will be useful for researchers and practitioners to realistically select proper method for their application.