作者：
Zahir, SNaqvi, MUNBC
Dept Comp Sci Image Proc Graph & Multimedia Lab Prince George BC Canada
In this paper, we propose a near minimum sparse pattern coding based scheme for binary image compression. Sparse patterns such as those obtained from prediction, image differencing, and other methods can be coded effi...
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ISBN:
(纸本)0780391349
In this paper, we propose a near minimum sparse pattern coding based scheme for binary image compression. Sparse patterns such as those obtained from prediction, image differencing, and other methods can be coded efficiently using the scheme proposed in this paper. In this research we apply our scheme on coordinate representation of rectangular regions via a number of matrices. Such representations allow for efficiently coding these vertices, and hence compress the image significantly. Simulation results show that the proposed scheme outperformed previously published methods for coordinate data coding by nearly 17%. This scheme has low complexity compared with JBIG2.
A new method for coding and lossless compression of gray scale images has been proposed. After coding of intensities, a prediction process is performed followed by the mapping of prediction residuals that are split in...
详细信息
ISBN:
(纸本)0819444073
A new method for coding and lossless compression of gray scale images has been proposed. After coding of intensities, a prediction process is performed followed by the mapping of prediction residuals that are split into bit planes to which the compression technique is applied, The planes can be coded as uncompressed or compressed using a variable block-size segmentation and coding. The used coding and compression schemes include minterm coding, coordinate data coding, discrete multiple-valued input binary functions, basic Walsh, triangular, Reed-Muller weights and spectra and the reference row technique. Experimental results show that the described method has comparable compression ratios when compared with other compression techniques.
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