We present a subspace learning method, called Local Discriminant Embedding with Tensor representation (LDET), that addresses simultaneously the generalization and data representat...
Following a recently introduced perceptual model for balanced multiwavelets, we outline, in this paper, an extension of our previous work and propose a new perceptual model for sca...
We present a probabilistic approach to shape matching which is invariant to rotation, translation and scaling. Shapes are represented by unlabeled point sets, so discontinuous bou...
The primary goal of image steganography techniques has been to maximize embedding rate while minimizing the detectability of the resulting stego images against steganalysis techni...
Linear techniques are widely used to reduce the dimension of image representation spaces in applications such as image indexing and object recognition. Optimal Component Analysis ...
Yiming Wu, Xiuwen Liu, Washington Mio, Kyle A. Gal...
SP-frame is a new picture type supported by H.264, and supports functions such as rate-switching and random-access. In this paper, we investigate several complementary methods to ...
We propose here a new pointwise wavelet thresholding function that incorporates inter-scale dependencies. This non-linear function depends on a set of four linear parameters per s...
An important class of image data sets depict an object undergoing deformation. When there are only a few underlying causes of the deformation, these images have a natural lowdimen...
This paper presents separation of specular and diffuse reflection components from an image pair. The proposed approach is based on the dichromatic reflectance model and Markov ran...
Sang Hwa Lee, Hyung il Koo, Nam Ik Cho, Jong-Il Pa...