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Improved Hyperspectral Image Testing Using Synthetic Imagery and Factorial Designed Experiments

Name: Improved Hyperspectral Image Testing Using Synthetic Imagery and Factorial Designed Experiments
Brand: Biblioscholar
SKU: 08249232
Price: 21875 HUF
Availability: InStock
Author: Joseph P Bellucci
ISBN: 9781288395408

Joseph P Bellucci

Language

English

Book Paperback

Libristo code: 08249232

Publishers Biblioscholar, December 2012

The goal of any remote sensing system is to gather data about the geography it is imaging. In order... Full description

Libristo code: 08249232

147 b

21 875 Ft

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The goal of any remote sensing system is to gather data about the geography it is imaging. In order to gain knowledge of the earth's landscape, post-processing algorithms are developed to extract information from the collected data. The algorithms can be intended to classify the various ground covers in a scene, identify specific targets of interest, or detect anomalies in an image. After the design of an algorithm comes the difficult task of testing and evaluating its performance. Traditionally, algorithms are tested using sets of extensively ground truthed test images. However, the lack of well characterized test data sets and the significant cost and time issues associated with assembling the data sets contribute to the limitations to this approach. This thesis uses a synthetic image generation model in cooperation with a factorial designed experiment to create a family of images with which to rigorously test the performance of hyperspectral algorithms.