A high performance Interactive Image SpreadSheet (IISS)

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New methods are needed for visualizing, interpreting, comparing, organizing, and analyzing immense multispectral satellite datasets. The traditional numerical spreadsheet paradigm has been extended to develop a new scientific visualization approach for processing multisensor image datasets interactively. Exploring the advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing tasks is the objective of the Interactive Image SpreadSheet (IISS) project at Goddard Space Flight Center. In the IISS each cell can display any portion of an original or calculated image, a projection of a multidimensional dataset such as a 3‐D surface, a glyph (graphic symbol) representing an image, digitized maps, digital terrain models, graphs, or vector drawings. The term image is used in a general sense to refer to any 2‐D multisource dataset. The IISS typically contains an array of image cells of arbitrary size each of which can contain one or more frames (images). The user can scroll or page through this multidimensional cube of frames along any dimension. The IISS emphasizes an immediate visual approach to interacting with data. A unique capability that the IISS provides are the highly interactive browsing tools, accessible through a graphical user interface, for effectively inspecting large sets of image arrays using synchronized cell level operations such as zoom, roam, animation, and function execution.The IISS combines the quantitative aspects of a numerical spreadsheet with powerful visualization tools to enable an investigator to easily experiment with various combinations of multispectral image data using a library of standard algorithms and to interactively develop custom algorithms. Remotely sensed datasets from multispectral instruments on satellites such as GOES, NOAA, Nimbus, DMSP, and Landsat have been used to develop and evaluate the functionality of the IISS. Formula expressions for creating color composites, implementing image enhancements, calculating vegetation indices, viewing perspective and stereo imagery have been developed using multispectral data. The IISS can also be used in a variety of imaging disciplines that routinely need to organize and manipulate large volumes of visual data including numerical simulation data, observational field data, astronomical imaging, biomedical imaging, computer vision and manufacturing robotics, business document imaging, and multimedia. The practical realization of the computationally challenging IISS project relies on the fact that personal superworkstations have become inexpensive enough that one can extend the interactive scalar spreadsheet concept to the image processing field. The hardware features that make this possible include multiple processors, large amounts of general purpose memory, high‐performance data buses, large mass storage, and pipelined or other advanced architectures for graphics and image operations. The need for increasingly more interactive imaging and visualization applications using high definition displays in collaborative environments will continue to drive the demand for more powerful hardware features and information network capabilities that are widely accessible.