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Divisive normalization has been recognized as a successful approach to model the perceptual sensitivity of biological vision. It also provides a useful image representation that is well-matched to the statistical properties of natural images. Here we propose a reduced- reference image quality assessment method in the divisive normalization transform domain, where the quality of an image is evaluated...
Recently, locality sensitive discriminant analysis (LSDA) was proposed for dimensionality reduction. As far as matrix data, such as images, they are often vectorized for LSDA algorithm to find the intrinsic manifold structure. Such a matrix-to-vector transform may cause the loss of some structural information residing in original 2D images. Firstly, this paper proposes an algorithm named two-dimensional...
In this paper we propose features based on sub-space projection methods using Principal Component Analysis (PCA) and Independent Component Analysis (ICA) on wavelet sub-band for face recognition. Wavelet based sub-band decomposition helps to reduce the size of image, and the approximate image obtained in the low-low (approximate) band is used here to apply sub-space projection methods. This improves...
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