Title :
A method for object identification in multispectral image based on tensor approach
Author :
Lefei Zhang ; Xin Huang ; Bo Du ; Liangpei Zhang
Author_Institution :
LIESMARS, China
Abstract :
In this paper, we propose a new approach for multispectral image object identification using a proximal support tensor machine. The image object is represented as a 3-order tensor that encodes both the spectral and neighborhood spatial information, and then applies the proximal support tensor machine (PSTM) for object identification. Experiments demonstrate that by comparison with the support tensor machine (STM) and conventional support vector machine (SVM), the proposed PSTM reduces the false alarm rate and training time while keeps the 100% identification rate, which indicates that PSTM is an effective method for multispectral image object identification.
Keywords :
geophysical image processing; object detection; support vector machines; tensors; 3-order tensor; PSTM; SVM; multispectral image object identification; neighborhood spatial information; proximal support tensor machine; spectral information; support vector machine; tensor approach; Abstracts; Bit error rate; Educational institutions; Reflectivity; Soil; Support vector machines; Tensile stress; Multispectral; Object Identification; Support Vector Machine; Tensor;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2012 4th Workshop on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3405-8
DOI :
10.1109/WHISPERS.2012.6874268