Title of article :
An oblique subspace projection approach for mixed pixel classification in hyperspectral images
Author/Authors :
Chang، Chein-I نويسنده , , Tu، Te-Ming نويسنده , , Shyu، Hsuen-Chyun نويسنده , , Lee، Ching-Hai نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 1999
Pages :
-1398
From page :
1399
To page :
0
Abstract :
This paper presents a technique for obtaining the distance of a step edge from the lens of a camera using a single defocused image of that edge. The proposed technique does not suffer from the correspondence and occlusion problems associated with methods based on multiple images. The technique employs a Multi-Layer Perceptron network trained by backpropagation to compute distances from derivative images of blurred edges. The paper gives experimental results which clearly show the accuracy of the proposed technique. (C) 1999 Published by Elsevier Science Ltd on behalf of the Pattern Recognition Society. All rights reserved.
Keywords :
Least-squares estimate , Neyman-Pearson detection , ROC curve , Orthogonal subspace projection , Oblique subspace projection
Journal title :
PATTERN RECOGNITION
Serial Year :
1999
Journal title :
PATTERN RECOGNITION
Record number :
14548
Link To Document :
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