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HIGH PERFORMANCE PHOTOGRAMMETRIC
PROCESSING ON COMPUTER CLUSTERS
V. N. Adrov, M. A. Drakin, A. Yu. Sechin
JCSC Racurs, Moscow, Russia - adrov@racurs.ru, mike@racurs.ru, sechin@racurs.ru
Commission IV/3: Mapping from High Resolution Data
KEY WORDS: Satellites, DEM, Digital, Model, Mosaic, Networks, Orthoimage, Orthorectification, Photogrammetry
ABSTRACT:
Most cpu consuming tasks in photogrammetric processing can be done in parallel. The algorithms take independent bits as input and
produce independent bits as output. The independence of bits comes from the nature of such algorithms since images, stereopairs or
small image blocks parts can be processed independently. Many photogrammetric algorithms are fully automatic and do not require
human interference. Photogrammetric workstations can perform tie points measurements, DTM calculations, orthophoto
construction, mosaicing and many other service operations in parallel using distributed calculations. Distributed calculations save
time reducing several days calculations to several hours calculations. Modern trends in computer technology show the increase of
cpu cores in workstations, speed increase in local networks, and as a result dropping the price of the supercomputers or computer
clusters that can contain hundreds or even thousands of computing nodes. Common distributed processing in DPW is usually
targeted for interactive work with a limited number of cpu cores and is not optimized for centralized administration. The bottleneck
of common distributed computing in photogrammetry can be in the limited lan throughput and storage performance, since the
processing of huge amounts of large raster images is needed.
1. INTRODUCTION
Many operations in processing remote sensing data can be split
into numerous tasks that can be easily done in parallel.
Figure 1. Building orthomosaic from a set of images
Figure 2. Conventional approach: many workstations and one
The original images are similar in nature and can be processed server
independently to build ortho mosaics. This is due to the fact that
cutlines calculation, orthorectification, image format
conversion, pansharpening, many service opertations performed are used.
on one image or on few images and are independent on other
images. Parallel processing of data can reduce the computer
This approach is not efficient when modern computer clusters
2. DISTRIBUTED PROCESSING ON
time needed to get the final result considerably. The current COMUTER CLUSTERS
trends in computer hardware are the increasing number of cores Special adjustments of software algorithms are needed for
(identical computer units) on the off-the-shelf CPUs, larger and computer clusters. Such algorithms predict data workflow and
faster computer networks and more and more affordable split the computing tasks into several independent processes.
supercomputers as clusters of thousands of computer nodes. The approach is different from the conventional one: the main
Conventional digital photogrammetric workstation (DPWs) use ideology is: one workstation and multiple servers
distributed processing that is based on interactive work and uses
the ideology — many workstations and one server.
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