An automated parallel image registration technique based on the correlation of wavelet features
ABSTRACT With the increasing importance of multiple multiplatform remote sensing missions, fast and automatic integration of digital data from disparate sources has become critical to the success of these endeavors. Our work utilizes maxima of wavelet coefficients to form the basic features of a correlation-based automatic registration algorithm. Our wavelet-based registration algorithm is tested successfully with data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and the Landsat Thematic Mapper (TM), which differ by translation and/or rotation. By the choice of high-frequency wavelet features, this method is similar to an edge-based correlation method, but by exploiting the multiresolution nature of a wavelet decomposition, our method achieves higher computational speeds for comparable accuracies. This algorithm has been implemented on a single-instruction multiple-data (SIMD) massively parallel computer, the MasPar MP-2, as well as on the CrayT3D, the Cray T3E, and a Beowulf cluster of Pentium workstations.
Conference Paper: Parallel Multi-Temporal Remote Sensing Image Change Detection on GPU[Show abstract] [Hide abstract]
ABSTRACT: Change detection is an important technique in damage assessment area. As the amount of remote sensing images and the complexity of algorithms rise, the demand for processing power is increasing. In this paper, we propose PLog-FLCM, a parallel algorithm for change detection. It is implemented on AMD Accelerated Parallel Processing (APP) SDK v2 based on Open Computing Language. The parallel characteristics and implementation details of the proposed PLog-FLICM algorithm are presented. Experiments on several Synthetic Aperture Radar(SAR) images demonstrate that the proposed algorithm outperform other algorithms, and the designed parallel algorithm can greatly reduce the computational time of change detection algorithm. It has achieved speedups of between 63 and 145 times on AMD Radeon HD 6870 Graphics Processing Unit (GPU).Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2012 IEEE 26th International; 01/2012
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ABSTRACT: Investigation of urban built environment includes a wide range of applications that require 3-D information. New approaches are needed for near-real-time analysis of the urban environment with natural 3-D visualisation of extensive coverage. Hyperspectral remote sensing technology is a promising and powerful tool to assess quantitative classification of urban materials by exploring possible chemical/physical changes using spectral information across the VIS-NIR-SWIR spectral region. Light Detection And Ranging (LiDAR) technology offers precise information about the geometrical properties of the surfaces and can reflect the different shapes and formations in the complex urban environment. Generating a monitoring system that is based on integrative fusion of hyperspectral and LiDAR data may enlarge the application envelope of each individual technology and contribute valuable information on urban built environments and planning. A fusion process defined by a data-registration algorithm and including spectral/spatial and 3-D information is developed and presented. The proposed practical 3-D urban environment application for photogrammetric and urban planning purposes integrates the hyperspectral (spectrometer, ground camera and airborne sensor) and LiDAR data. This application may provide urban planners, civil engineers and decision-makers with tools to consider quantitative spectral information in the 3-D urban space.International Journal of Image and Data Fusion. 01/2013; 4(1).
- 08/2009; Wiley., ISBN: 978-0470040393