Hybrid classification using combination of optimized spectral angle mapping algorithm and interpolation method on multispectral and hyper spectral image

A growing number of studies in recent years has focused on improvement of performance of classification algorithm on hyper-spectral image; this provides a scientific basis for efficient object detection. This paper tries to improve the performance of spectral angle mapping algorithm to classify the...

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Bibliographic Details
Published in:2012 International Conference on Computing, Communication and Applications pp. 1 - 4
Main Authors: Tembhurne, O. W., Malik, L. G.
Format: Conference Proceeding
Language:English
Published: IEEE 01.02.2012
Subjects:
Algorithm design and analysis
Classification algorithms
Clustering algorithms
Hyper-spectral imagery
Indexes
Interpolation
Interpolation method
Object detection
SAM algorithm
supervised cluster analysis
Vectors
ISBN:1467302708, 9781467302708
ISSN:2325-6001
Online Access:Get full text
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Summary:A growing number of studies in recent years has focused on improvement of performance of classification algorithm on hyper-spectral image; this provides a scientific basis for efficient object detection. This paper tries to improve the performance of spectral angle mapping algorithm to classify the hyper-spectral image. The proposed method uses combination of spectral angle mapping algorithm and interpolation method with supervised clustering techniques for efficient object detection and region finding. Spectral angle mapping algorithm is used for finding pure pixel, thereby reducing the probability of false object detection due to geometric errors. The experimental results show that, proposed hybrid technique reduces the probability of false object detection with inbuilt radiometric error enhancement capability for hyper-spectral image.
ISBN:1467302708
9781467302708
ISSN:2325-6001
DOI:10.1109/ICCCA.2012.6179210