Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification

The employed dictionary plays an important role in sparse representation or sparse coding based image reconstruction and classification, while learning dictionaries from the training data has led to state-of-the-art results in image classification tasks. However, many dictionary learning models expl...

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Bibliographic Details
Published in:	International journal of computer vision Vol. 109; no. 3; pp. 209 - 232
Main Authors:	Yang, Meng, Zhang, Lei, Feng, Xiangchu, Zhang, David
Format:	Journal Article
Language:	English
Published:	Boston Springer US 01.09.2014 Springer Springer Nature B.V
Subjects:	Analysis Applied sciences Artificial Intelligence Classification Coding, codes Computer Imaging Computer Science Computer science; control theory; systems Detection, estimation, filtering, equalization, prediction Dictionaries Discrimination Exact sciences and technology Fourier transforms Image classification Image Processing and Computer Vision Information, signal and communications theory Learning Learning and adaptive systems Machine learning Mathematical models Pattern Recognition Pattern Recognition and Graphics Pattern recognition. Digital image processing. Computational geometry Principal components analysis Representations Signal and communications theory Signal, noise Sparsity Studies Tasks Teaching methods Telecommunications and information theory Vision Sparse representation Fisher criterion Dictionary learning Image classification Classification scheme Computer vision Dictionaries Image processing Sparse coding Modeling Fisher information Image coding Discrimination Fisher test Learning algorithm Artificial intelligence
ISSN:	0920-5691, 1573-1405
Online Access:	Get full text
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