Accelerating SAR Image Registration Using Swarm-Intelligent GPU Parallelization
نویسندگان
چکیده
منابع مشابه
Accelerating Depth Image-Based Rendering Using GPU
In this paper, we propose a practical method for hardwareaccelerated rendering of the depth image-based representation (DIBR) object, which is defined in MPEG-4 Animation Framework eXtension (AFX). The proposed method overcomes the drawbacks of the conventional rendering, i.e. it is slow since it is hardly assisted by graphics hardware and surface lighting is static. Utilizing the new features ...
متن کاملAccelerating Protein Structure Prediction using Particle Swarm Optimization on GPU
Protein tertiary structure prediction (PSP) is one of the most challenging problems in bioinformatics. Different methods have been introduced to solve this problem so far, but PSP is computationally intensive and belongs to the NP-hard class. One of the best solutions to accelerate PSP is the use of a massively parallel processing architecture, such graphical processing unit (GPU), which is use...
متن کاملAccelerating parallel particle swarm optimization via GPU
This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date...
متن کاملStructure-driven SAR image registration
We present a fully automatic method for the alignment SAR images, which is capable of precise and robust alignment. A multiresolution SAR image matching metric is first used to automatically determine tie-points, which are then used to perform coarse-to-fine resolution image alignment. A formalism is developed for the automatic determination of tie-point regions that contain sufficiently distin...
متن کاملAccelerating Image Retrieval Using Factorial Correspondence Analysis on GPU
We are interested in the intensive use of Factorial Correspondence Analysis (FCA) for large-scale content-based image retrieval. Factorial Correspondence Analysis, is a useful method for analyzing textual data, and we adapt it to images using the SIFT local descriptors. FCA is used to reduce dimensions and to limit the number of images to be considered during the search. Graphics Processing Uni...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2020
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2020.3024899