In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extr...
Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellap...
The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse codingbased image super-resolution. Sparse coding is a typical unsupervi...
We present a new, block-based image codec based on sparse representations using a learned, structured dictionary called the IterationTuned and Aligned Dictionary (ITAD). The quest...
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 ...
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma