Parallel storage and retrieval of pixmap images

To fulfill the requirement of rapid access to huge amounts of uncompressed pixmap image data, a parallel image server architecture is proposed, based on arrays of intelligent disk nodes, with each disk node composed of one processor and one disk. It is shown how images can be partitioned into extents and efficiently distributed among available intelligent disk nodes. The image server's performance is analyzed according to various parameters such as the number of cooperating disk nodes, the sizes of image file extents, the available communication throughput, and the processing power of disk node and image server processors. Important image access speed improvements are obtained by image extent caching and image part extraction in disk nodes. With T800 transputer-based technology, a system composed of eight disk nodes offers access to three full-color 512×512 pixmap image parts per second (2.4 megabytes per second). For the same configuration but with the recently announced T9000 transputer, image access throughput is eight images per second (6.8 megabytes per second

Multimedia performance behavior of the GigaView parallel image server

Multimedia interfaces increase the need for large image databases, supporting the capability of storing and fetching streams of data with strict synchronicity and isochronicity requirements. In order to fulfill these requirements, the GigaView parallel image server architecture relies on arrays of intelligent disk nodes, with each disk node being composed of one processor and one disk. This paper analyzes, through simulation, the real-time behavior of the GigaView in terms of delay and delay jitter. For a high-end GigaView architecture, consisting of 16 disks and T9000 transputers, we evaluate stream frame access times under various parameters, such as load factors, frame size, stream throughput, and synchronicity requirement

Giga view parallel image server performance analysis

Professionals in various fields such as medical imaging, biology and civil engineering require rapid access to huge amounts of uncompressed pixmap image data. Multi-media interfaces further increase the need for large image databases. In order to fulfill these requirements, the GigaView parallel image server architecture relies on arrays of intelligent disk nodes, each disk node being composed of one processor and one disk. This contribution analyzes through simulation and experimentation the behavior of the GigaView under single and multiple requests, and compares it to the behavior of RAID servers. It evaluates image visualization window access times under various parameters such as load factors and the number of cooperating disk nodes. Under single request, the GigaView image server can be modeled as a single high-throughput low-latency secondary storage device. Under multiple requests, the notions of utilization and maximum sustainable throughput define accurately the behavior of the GigaView

Comparing multimedia storage architectures

Multimedia interfaces increase the need for large image databases, capable of storing and reading streams of data with strict synchronicity and isochronicity requirements. In order to fulfil these requirements, we use a parallel image server architecture which relies on arrays of intelligent disk nodes, each disk node being composed of one processor and one or more disks. This contribution analyzes through simulation the real-time behavior of two multiprocessor multi-disk architectures: GigaView and the Unix workstation cluster. GigaView incorporates point-to-point communication between processing units and the workstation cluster supports communication through a shared bus-and-memory architecture. For a standard multimedia server architecture consisting of 8 disks and 4 disk-node processors, we evaluate stream frame access times under various parameters such as load factors, frame size, stream throughput and synchronicity requirements. We compare the behavior of GigaView and the workstation cluster in terms of delay and delay jitte

Evaluation of pointer click relevance feedback in PicSOM : deliverable D1.2 of FP7 project nº 216529 PinView

This report presents the results of a series of experiments where knowledge of the most relevant part of images is given as additional information to a content-based image retrieval system. The most relevant parts have been identified by search-task-dependent pointer clicks on the images. As such they provide a rudimentary form of explicit enriched relevance feedback and to some extent mimic genuine implicit eye movement measurements which are essential ingredients of the PinView project

A quadtree approach to parallel image processing

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 93-95).by Hany S. Saleeb.M.Eng

Synthesizing parallel imaging applications using the CAP Computer-Aided Parallelization tool

Imaging applications such as filtering, image transforms and compression/decompression require vast amounts of computing power when applied to large data sets. These applications would potentially benefit from the use of parallel processing. However, dedicated parallel computers are expensive and their processing power per node lags behind that of the most recent commodity components. Furthermore, developing parallel applications remains a difficult task. In order to facilitate the development of parallel applications, we propose the CAP computer aided parallelization tool which enables application programmers to specify at a high level of abstraction the flow of data between pipelined parallel operations. In addition, the CAP tool supports the programmer in developing parallel imaging and storage operations. CAP enables combining efficiently parallel storage access routines and image processing sequential operations. The paper shows how processing and I/O intensive imaging applications must be implemented to take advantage of parallelism and pipelining between data access and processing. The paper's contribution is: (1) to show how such implementations can be compactly specified in CAP; and (2) to demonstrate that CAP specified applications achieve the performance of custom parallel code. The paper analyzes theoretically the performance of CAP specified applications and demonstrates the accuracy of the theoretical analysis through experimental measurement

Algorithms and Data Structures for Automated Change Detection and Classification of Sidescan Sonar Imagery

During Mine Warfare (MIW) operations, MIW analysts perform change detection by visually comparing historical sidescan sonar imagery (SSI) collected by a sidescan sonar with recently collected SSI in an attempt to identify objects (which might be explosive mines) placed at sea since the last time the area was surveyed. This dissertation presents a data structure and three algorithms, developed by the author, that are part of an automated change detection and classification (ACDC) system. MIW analysts at the Naval Oceanographic Office, to reduce the amount of time to perform change detection, are currently using ACDC. The dissertation introductory chapter gives background information on change detection, ACDC, and describes how SSI is produced from raw sonar data. Chapter 2 presents the author\u27s Geospatial Bitmap (GB) data structure, which is capable of storing information geographically and is utilized by the three algorithms. This chapter shows that a GB data structure used in a polygon-smoothing algorithm ran between 1.3 – 48.4x faster than a sparse matrix data structure. Chapter 3 describes the GB clustering algorithm, which is the author\u27s repeatable, order-independent method for clustering. Results from tests performed in this chapter show that the time to cluster a set of points is not affected by the distribution or the order of the points. In Chapter 4, the author presents his real-time computer-aided detection (CAD) algorithm that automatically detects mine-like objects on the seafloor in SSI. The author ran his GB-based CAD algorithm on real SSI data, and results of these tests indicate that his real-time CAD algorithm performs comparably to or better than other non-real-time CAD algorithms. The author presents his computer-aided search (CAS) algorithm in Chapter 5. CAS helps MIW analysts locate mine-like features that are geospatially close to previously detected features. A comparison between the CAS and a great circle distance algorithm shows that the CAS performs geospatial searching 1.75x faster on large data sets. Finally, the concluding chapter of this dissertation gives important details on how the completed ACDC system will function, and discusses the author\u27s future research to develop additional algorithms and data structures for ACDC

Research into language concepts for the mission control center

A final report is given on research into language concepts for the Mission Control Center (MCC). The Specification Driven Language research is described. The state of the image processing field and how image processing techniques could be applied toward automating the generation of the language known as COmputation Development Environment (CODE or Comp Builder) are discussed. Also described is the development of a flight certified compiler for Comps