Matching pursuits over a basis of separable Gabor functions has been demonstrated to outperform DCT methods for displaced frame difference coding for video compression. Unfortunately, apart from very low bit-rate applications, the algorithm involves an extremely high computational load. This paper contains an original contribution to the issues of dictionary selection and fast implementation for matching pursuits video coding. First, it is shown that the PSNR performance of existing matching pursuits codecs can be improved and the implementation cost reduced by a better selection of dictionary functions. Secondly, dictionary factorization is put forward to further reduce implementation costs. A reduction of the computational load by a factor of 20 is achieved compared to implementations reported to date. For a majority of test conditions, this reduction is supplemented by an improvement in reconstruction quality. Finally, a pruned full-search algorithm is introduced, which offers significant quality gains compared to the better-known heuristic fast-search algorithm, while keeping the computational cost low.

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Matching pursuits video coding: dictionaries and fast implementation

A method and device for coding multi-dimensional data using a codebook of basis functions; wherein said codebook comprises a subset of a larger multi-dimensional basis dictionary, said larger dictionary comprising separable combinations of one or more primary one dimensional basis function dictionaries, and a corresponding decoding method.

Matching pursuits coding of data

Briefly, in accordance with one embodiment, a method of designing a basis selection for matching pursuits is described.

Matching pursuits basis selection design

A method for determining whether portions of text have been copied during electronic copying, photocopying, or scanning of a document. The method comprises generating a target code from a target passage of the text, determining whether a sample passage of text includes the target code, and, upon successful determination, initiating an action if the sample passage of text includes the target code. A method of generating a code representative of a passage of text uses a spacing between respective occurrences of one or more key symbol strings within the text. By comparing the known code of a target text passage with the code generated from a sample text passage, it is easy to determine whether the target text has been used within the sample. The method may be integrated within a copying device.

Identification of text

Embodiments described herein may include example embodiments of a method, article and apparatus for compressing data utilizing combinatorial coding with specified occurrences which may be used for communicating between two or more components connected to an interconnection medium (e.g., a bus) within a single computer or digital data processing system, and/or for communication between computing platforms via a network or other interconnection medium.

Combinatorial coding/decoding with specified occurrences for electrical computers and digital data processing systems

In this paper, a novel multiresolution algorithm for low bit-rate image compression is presented. High quality low bit-rate image compression is achieved by first decomposing the image into approximation and detail subimages with a shift-orthogonal multiresolution analysis. Then, at the coarsest resolution level, the coefficients of the transformation are encoded by an orthogonal matching pursuit algorithm with a wavelet packet dictionary. Our dictionary consists of convolutional splines of up to order two for the detail and approximation subbands. The intercorrelation between the various resolutions is then exploited by using the same bases from the dictionary to encode the coefficients of the finer resolution bands at the corresponding spatial locations. To further exploit the spatial correlation of the coefficients, the zero trees of wavelets (EZW) algorithm was used to identify the potential zero trees. The coefficients of the presentation are then quantized and arithmetic encoded at each resolution, and packed into a scalable bit stream structure. Our new algorithm is highly bit-rate scalable, and performs better than the segmentation based matching pursuit and EZW encoders at lower bit rates, based on subjective image quality and peak signal-to-noise ratio.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A. J. Mirani

Papers

Low-bit-rate subband image coding with matching pursuits