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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jimenez, L. Landgrebe, D. |
| Copyright Year | 1994 |
| Description | Author affiliation: Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA (Jimenez, L.; Landgrebe, D.) |
| Abstract | The recent development of more sophisticated remote sensing systems enables the measurement of radiation in many more spectral intervals than previously possible. An example of that technology is the AVIRIS system, which collects image data in 220 bands. As a result of this, new algorithms must be developed in order to analyze the more complex data effectively. Data in a high dimensional space presents a substantial challenge, since intuitive concepts valid in a 2-3 dimensional space do not necessarily apply in higher dimensional spaces. For example, high dimensional space is mostly empty. This results from the concentration of data in the corners of hypercubes. Other examples may be cited. Such observations suggest the need to project data to a subspace of a much lower dimension on a problem specific basis in such a manner that information is not lost. Projection pursuit is a technique that will accomplish such a goal. Since it processes data in lower dimensions, it should avoid many of the difficulties of high dimensional spaces. The authors investigate some of the properties of projection pursuit. |
| Starting Page | 1145 |
| Ending Page | 1147 |
| File Size | 336967 |
| Page Count | 3 |
| File Format | |
| ISBN | 0780314972 |
| DOI | 10.1109/IGARSS.1994.399367 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1994-08-08 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Space technology Remote sensing Algorithm design and analysis Hypercubes |
| Content Type | Text |
| Resource Type | Article |
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