Abstract
In this paper, we prove that the principal component analysis (PCA) and the linear discriminant analysis (LDA) can be directly implemented in the wavelet cosine transform (DWT) domain and the results are exactly the same as the one obtained from the spatial domain. In some applications, compressed images are desirable to reduce the storage requirement. For images compressed using the DWT in JPEG2000 or MPEG4 standard, the PCA and LDA can be directly implemented in the DWT domain such that the inverse DWT transform can be skipped and the dimensionality of the original data can be initially reduced to cut down computation cost. Finally, It is verified by infrared face recognition based on PCA and LDA in DWT domain through our infrared face database.
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© 2012 Springer-Verlag Berlin Heidelberg
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Liu, Z., Fang, Z. (2012). PCA and FLD in DWT Domain. In: Pan, Z., Cheok, A.D., Müller, W., Chang, M., Zhang, M. (eds) Transactions on Edutainment VII. Lecture Notes in Computer Science, vol 7145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29050-3_18
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DOI: https://doi.org/10.1007/978-3-642-29050-3_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29049-7
Online ISBN: 978-3-642-29050-3
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