Samples, or (c) a second method based directly upon the discriminant functions.Īlso included are methods especially designed to search for narrow spectral features Measures, (b) a method based directly upon decision boundaries defined by training (a) searching for the best subset of features using any of five statistical distance Determine the best spectral features to use for a given classification using.A covariance estimation scheme (LOOC)Ĭan optimize that estimate for small training sets. Statistics" also allows one to improve the extent to which the defined class statisticsįit the composite of all data in the data set. Use in evaluating classification results quantitatively. Define classes via designating rectangular or polygonal training fields or mask image files, compute field and class statistics, and define test fields for.Use of clustering followed by ECHO spectral/spatial classification provides an effective multivariate scene segmentation scheme. Cluster statistics can also be saved as class statistics. Save the results for display as a thematic map. Cluster data using either a single pass or an iterative (isodata) clustering algorithm.The new channels may be the result of a principal components or feature extraction transformation of the existing ones, or they may result from the ratio of a linear combination of existing bands divided by a different linear combination of bands. Create new channels of data from existing channels.Reformat the data file in a number of ways, e.g., by adding a standard header, changing from any one of the three interleave formats to either of the other two, editing out channels, combining files, adding or modifying channel descriptions, mosaicing data sets, changing the geometry of a data set, and a number of other changes.Histogram data for use in determining the gray scale regime for a display.ArcView Shape Files may be overlain on the images. Display multispectral images in a variety of B/W or color formats using linear or equal area gray scales display (internally generated) thematic images also in B/W or color, with an ability to control the color used for each theme.In cases of two, four or eight bytes per sample, the bytes may be in either order. The data values may be 8-bit integer, 16-bit integer, 32-bit integer, 32-bit real or 64-bit real. Import data in either Binary or ASCII format with or without a header, and in Band Interleaved by Line (BIL), Band Sequential (BSQ), or Band Interleaved by Sample (BIS) formats.Capabilities of the current version of MultiSpec include New capabilities are continually added to MultiSpec as they emerge from our research Given the currentĬost/performance trends, even more cost-effective systems are likely to be available ![]() Minute using 12 bands and a Gaussian maximum likelihood scheme. Such a system is capable of classifying in excess of 6 million pixel-classes per A reasonably current generation, middle range machine andĬolor display, would have a street price of less than $2000 at the present time. System, called MultiSpec, has been implemented for the Apple Macintosh and PC-Windows Labs, and several commercially offered products are descendants of LARSYS. A number of systems in government laboratories, university research ![]() Remote sensing multispectral data processing systems, originally created during Of the LARSYS multispectral image data analysis system. ![]() The work of building the current capability began by implementing an upgraded version The system should provide for easy import of data in a variety of formats, and easyĮxport of results, both in thematic map and in tabular form.Using the most modern of software environments. The system should be easy to learn and easy to use, even for the infrequent user,.Researcher (i.e., computer platforms < $2000). The implementation should be on a readily available computer platform which hasĪdequate processing power, but is financially within the reach of any Earth science.MultiSpec satisfies the following design goals: There are currently in excess of several thousand Use in other applications such as multiband medical imagery and in K-12 and university Methods for analyzing such hyperspectral image data. Of MultiSpec is as an aid to export the results of our research into devising good The Landsat series of Earth satellites and hyperspectral image data from currentĪnd future airborne and spaceborne systems such as AVIRIS. MultiSpec (© Purdue Research Foundation) is a processing system for interactivelyĪnalyzing Earth observational multispectral image data such as that produced by
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