XVIIIth Congress: XVIIIth Congress

Kraus, Karl; Waldhäusl, Peter

Bibliographic data

Multivolume work

Persistent identifier:: 1667435949

Title:: XVIIIth Congress

Sub title:: Vienna, Austria 1996

Year of publication:: 1996

Place of publication:: Vienna

Publisher of the original:: Austrian Society of Surveying and Geoinformation

Identifier (digital):: 1667435949

Language:: English

Editor:: Kraus, Karl; Waldhäusl, Peter

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 18., 1996, Wien; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 18., 1996, Wien; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 18., 1996, Wien; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 18., 1996, Wien; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1667438379

Title:: XVIIIth Congress

Scope:: 449 Seiten

Year of publication:: 1996

Place of publication:: Vienna

Publisher of the original:: Austrian Society of Surveying and Geoinformation

Identifier (digital):: 1667438379

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(31,B2)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist anhand des Copyrightjahrs ermittelt.

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Kraus, Karl; Waldhäusl, Peter

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 18., 1996, Wien; International Society for Photogrammetry and Remote Sensing; International Society for Photogrammetry and Remote Sensing, Commission Instrumentation for Data Reduction and Analysis

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 18., 1996, Wien; International Society for Photogrammetry and Remote Sensing; International Society for Photogrammetry and Remote Sensing, Commission Instrumentation for Data Reduction and Analysis

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 18., 1996, Wien; International Society for Photogrammetry and Remote Sensing; International Society for Photogrammetry and Remote Sensing, Commission Instrumentation for Data Reduction and Analysis

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 18., 1996, Wien; International Society for Photogrammetry and Remote Sensing; International Society for Photogrammetry and Remote Sensing, Commission Instrumentation for Data Reduction and Analysis

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: IMAGE NAVIGATION FOR EMERGENCY RESPONSE (INFER) Loey Knapp, Senior Systems Analyst, [...] John Turek, Research Staff Member, [...] Patricia Andrews, Project Leader, [...] Christopher Elvidge, [...]

Document type:: Multivolume work

Structure type:: Chapter

required by the system results in a significant reduction in the overall cost of the system. At first blush it might seem that the cost associated with processing is higher when images are stored in a compressed format; however, this need not be the case. If the data are organized and stored in the appropriate fashion, the search process can be made more efficient and we do not need to analyze all ofthe information stored in the image in order to eliminate it from consideration. One of the primary ideas of our project is that it is possible to increase the speed of searching through images stored in a digital library while simultaneously reducing the storage requirements. The remainder of this section goes into more details on this topic. Compression techniques can be either “lossless” or “lossy”. A lossless compression scheme is one which guarantees perfect reconstruction of all of the bits in the original dataset. A lossy compression scheme, on the other hand, does not reconstruct most images exactly but rather allows the loss of some informa- tion in order to achieve higher compression ratios. The end-user requirements determine whether lossy or lossless compression schemes can be used. As discussed below, our analysis scheme takes advantage of the properties introduced by lossy compression. However, remote sense scientists are reluctant to lose any data and, therefore, demand lossless compression. The compression scheme we use for image storage offers a hybrid solution. In order to address this issue, we employ a wavelet-based scheme that allows us to progressively extract image content by specifying both spatial and spectral constraints. Typically, as we relax the spectral con- straints we tighten the spatial constraints. However, if one fully relaxes both constraints the output is a lossless representation of the original image. The overall compression ratio achieved by this scheme is competitive with the best lossless compression schemes we have analyzed to date. In general, applying query and retrieval operations directly on lossily compressed data leads to improved computational effi- ciencies along two fronts: » One needs to process fewer bits; » The features and properties of the data are emphasized by the transformed-based compression. Query operations including retrieval, evaluation, transmission and visualization of the image (or video) data can be staged pro- gressively, by selectively and adaptively processing limited amounts of information, to minimize the total execution time. The difficulties that get introduced are twofold: * As the number of coefficients is reduced, dimensionality of the search space is reduced, resulting in many-to-one map- ping. Thus, the number of false hits increases. * The reduction of coefficients implied by the compression results in alignment errors. The net result is that the output produced by the operation may not match the exact value produced by operating directly on the original image. * We have developed techniques that, for several operations, allow us to quantify the latter effect without having to con- vert back to the spatial domain. This allows us to guarantee 194 that the results of our filters are identical to those produced by operating directly on the full image. Access via Internet Access to and dissemination of the data in the INFER project is provided via the Internet so data management techniques which improve access, search, and retrieval time, interactive visualiza- tion techniques, and a Netscape-based user interface are all inte- gral components of the system. While each of these components could be discussed at length, this paper will focus on only one - that of the need for a more complex, or ‘smart’ user interface in an Internet context. Through development of the INFER prototype it has become clear that an extremely critical component of an internet applica- tion is the user interface. In a local software system, the user interface must be intuitive enough for a user to navigate easily through the system functionality but, in general, a user working with in-house applications has an understanding of the underly- ing data. As we move to Internet-based applications it is important to con- sider the fact that the users are, in effect, logging on to a black box, with little or no knowledge of either system functionality or server databases. In the case of providing a data archive search capability it is essential that the user interface assist the user in understanding both the search functions and the extent of the data available for search. In effect, the result must be a ‘smart’ user interface. In a simple browse of a large data archive this means supplying the user with information on the spatial and temporal extent of the data. In an application scenario the problem becomes much more complex. For instance, in the context of a content-based search the user must be able to understand and specify the fol- lowing individual components of the search and their interrela- tionships: . Possible search features or search tools - this can be equated to the ‘fields’ in a database. ° The data sets available for search, e.g. AVHRR, DMSP. ° The temporal extent of the data sets. ° The spatial extent of the data sets. Providing this information to the user can present a user inter- face problem as user selections will progressively change the nature ofthe available data. For instance, specific search features may only be supported in a subset of the data; by selecting to search on that feature the user must be notified of the potential spatial and temporal extent of the search. On the other hand, beginning a search by selecting a spatial area may constrain the user to a subset of the search features. Essentially, wherever the user starts the search the information relative to the other three components may change and notification is required. The user would also be interested in knowing what ancillary data sets are available for background information or for complex searches. For instance, the user might want to view the results of a search for fires relative to topography or may want to actually International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B2. Vienna 1996 con gra Uni and infc fac: opti ofs but Pro dep One cod latic Thi nati bas For seat pot rest forr INF IBN exaı wilc rese date cati ing pop able resp tion ing | Wil bilit and bou atio! patc to fz ther nati arch fire mat mul data arie: mod earlı fire |

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