A Mixed Transform Approach For Efficient Compression Of Medical Images

    Authors

    A. Ramaswamy;W. B. Mikhael

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    IEEE Trans. Med. Imaging

    Keywords

    COSINE-TRANSFORM; Computer Science, Interdisciplinary Applications; Engineering, ; Biomedical; Engineering, Electrical & Electronic; Imaging Science &; Photographic Technology; Radiology, Nuclear Medicine & Medical Imaging

    Abstract

    A novel technique is presented to compress medical data employing two or more mutually nonorthogonal transforms, Both lossy and lossless compression implementations are considered, The signal is first resolved into subsignals such that each subsignal is compactly represented in a particular transform domain. An efficient lossy representation of the signal is achieved by superimposing the dominant coefficients corresponding to each subsignal, The residual error, which is the difference between the original signal and the reconstructed signal is properly formulated, Adaptive algorithms in conjunction with an optimization strategy are developed to minimize this error. Both two-dimensional (2-D) and three-dimensional (3-D) approaches for the technique are developed, It is shown that for a given number of retained coefficients, the discrete cosine transform (DCT)-Walsh mixed transform representation yields a more compact representation than using DCT or Walsh alone. This lossy technique is further extended for the lossless case, The coefficients are quantized and the signal is reconstructed, The resulting reconstructed signal samples are rounded to the nearest integer and the modified residual error is computed, This error is transmitted employing a lossless technique such as the Huffman coding, It is shown that for a given number of retained coefficients, the mixed transforms again produces the smaller rms-modified residual error, The first-order entropy of the error is also smaller for the mixed-transforms technique than for the DCT, thus resulting in smaller length Huffman codes.

    Journal Title

    Ieee Transactions on Medical Imaging

    Volume

    15

    Issue/Number

    3

    Publication Date

    1-1-1996

    Document Type

    Article

    Language

    English

    First Page

    343

    Last Page

    352

    WOS Identifier

    WOS:A1996UN48300012

    ISSN

    0278-0062

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