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DCC
2011
IEEE
9 years 9 months ago
Color Image Compression Using a Learned Dictionary of Pairs of Orthonormal Bases
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 ...
Xin Hou, Karthik S. Gurumoorthy, Ajit Rajwade
ICIP
2001
IEEE
11 years 4 months ago
On sparse signal representations
An elementary proof of a basic uncertainty principle concerning pairs of representations of ?? vectors in different orthonormal bases is provided. The result, slightly stronger th...
Michael Elad, Alfred M. Bruckstein
ICASSP
2011
IEEE
9 years 6 months ago
Image compression using the Iteration-Tuned and Aligned Dictionary
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...
Joaquin Zepeda, Christine Guillemot, Ewa Kijak
TIP
2010
255views more  TIP 2010»
9 years 9 months ago
Image Super-Resolution Via Sparse Representation
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
CORR
2011
Springer
186views Education» more  CORR 2011»
9 years 6 months ago
Blind Compressed Sensing Over a Structured Union of Subspaces
—This paper addresses the problem of simultaneous signal recovery and dictionary learning based on compressive measurements. Multiple signals are analyzed jointly, with multiple ...
Jorge Silva, Minhua Chen, Yonina C. Eldar, Guiller...
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