Multidimensional signal compression using multiscale recurrent patterns
Signal Processing - Image and Video Coding beyond Standards
Grayscale true two-dimensional dictionary-based image compression
Journal of Visual Communication and Image Representation
Image compression via textual substitution
WSEAS Transactions on Information Science and Applications
Textual substitution methods for image compression
ICAI'09 Proceedings of the 10th WSEAS international conference on Automation & information
Scanned compound document encoding using multiscale recurrent patterns
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Improved approximation bounds for planar point pattern matching
WADS'05 Proceedings of the 9th international conference on Algorithms and Data Structures
Complexity-compression tradeoffs in lossy compression via efficient random codebooks and databases
Problems of Information Transmission
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We propose a lossy data compression framework based on an approximate two-dimensional (2D) pattern matching (2D-PMC) extension of the Lempel-Ziv (1977, 1978) lossless scheme. This framework forms the basis upon which higher level schemes relying on differential coding, frequency domain techniques, prediction, and other methods can be built. We apply our pattern matching framework to image and video compression and report on theoretical and experimental results. Theoretically, we show that the fixed database model used for video compression leads to suboptimal but computationally efficient performance. The compression ratio of this model is shown to tend to the generalized entropy. For image compression, we use a growing database model for which we provide an approximate analysis. The implementation of 2D-PMC is a challenging problem from the algorithmic point of view. We use a range of techniques and data structures such as k-d trees, generalized run length coding, adaptive arithmetic coding, and variable and adaptive maximum distortion level to achieve good compression ratios at high compression speeds. We demonstrate bit rates in the range of 0.25-0.5 bpp for high-quality images and data rates in the range of 0.15-0.5 Mbps for a baseline video compression scheme that does not use any prediction or interpolation. We also demonstrate that this asymmetric compression scheme is capable of extremely fast decompression making it particularly suitable for networked multimedia applications