Compared to Singular Value Decomposition (SVD), Generalized Low Rank Approximations of Matrices (GLRAM) can consume less computation time, obtain higher compression ratio, and yiel...
Quantization index modulation is one of the best methods for performing blind watermarking, due to its simplicity and good rate-distortion-robustness tradeoffs. In this paper, a ne...
Vivekananda Bhat K., Indranil Sengupta, Abhijit Da...
We present a new color image compression algorithm for RGB images. In our previous work [6], we presented a machine learning technique to derive a dictionary of orthonormal basis ...
We propose an algorithm that predicts potentially missing Gene Ontology annotations, in order to speed up the time-consuming annotation curation process. The proposed method extend...
Marco Tagliasacchi, Roberto Sarati, Marco Masserol...
A no-reference image metric based on the singular value decomposition of local image gradients is proposed in this paper. This metric provides a quantitative measure of true image...
The calculation of a low-rank approximation of a matrix is a fundamental operation in many computer vision applications. The workhorse of this class of problems has long been the ...
The objective of this paper is to extend, in the context of multicore architectures, the concepts of tile algorithms [Buttari et al., 2007] for Cholesky, LU, QR factorizations to t...
We present a robust, hybrid non-blind MPEG video watermarking technique based on a high-order tensor singular value decomposition and the discrete wavelet transform (DWT). The core...
Emad E. Abdallah, A. Ben Hamza, Prabir Bhattachary...