Image compression using an edge adapted redundant dictionary and wavelets
Signal Processing - Sparse approximations in signal and image processing
Multiple description coding with redundant expansions and application to image communications
Journal on Image and Video Processing
Distributed multi-view image coding with learned dictionaries
Proceedings of the 5th International ICST Mobile Multimedia Communications Conference
Geometric video approximation using weighted matching pursuit
IEEE Transactions on Image Processing
Conditions for recovery of sparse signals correlated by local transforms
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Optimized atom position and coefficient coding for matching pursuit-based image compression
IEEE Transactions on Image Processing
A block based encoding algorithm for matching pursuit image coding
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Colour image coding with matching pursuit in the spatio-frequency domain
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Sparse representations for spatial prediction and texture refinement
Journal of Visual Communication and Image Representation
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Matching Pursuits with random sequential subdictionaries
Signal Processing
Statistical and signal-based network traffic recognition for anomaly detection
Expert Systems: The Journal of Knowledge Engineering
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New breakthroughs in image coding possibly lie in signal decomposition through nonseparable basis functions that can efficiently capture edge characteristics, present in natural images. The work proposed in this paper provides an adaptive way of representing images as a sum of two-dimensional features. It presents a low bit-rate image coding method based on a matching pursuit (MP) expansion, over a dictionary built on anisotropic refinement and rotation of contour-like atoms. This method is shown to provide, at low bit rates, results comparable to the state of the art in image compression, represented here by JPEG2000 and SPIHT, with generally a better visual quality in the MP scheme. The coding artifacts are less annoying than the ringing introduced by wavelets at very low bit rate, due to the smoothing performed by the basis functions used in the MP algorithm. In addition to good compression performances at low bit rates, the new coder has the advantage of producing highly flexible streams. They can easily be decoded at any spatial resolution, different from the original image, and the bitstream can be truncated at any point to match diverse bandwidth requirements. The spatial adaptivity is shown to be more flexible and less complex than transcoding operations generally applied to state of the art codec bitstreams. Due to both its ability for capturing the most important parts of multidimensional signals, and a flexible stream structure, the image coder proposed in this paper represents an interesting solution for low to medium rate image coding in visual communication applications.