Image interpolation using wavelet-based hidden Markov trees

K. Kinebuchi, D. D. Muresan, T. W. Parks

    Research output: Contribution to journalConference articlepeer-review

    86 Scopus citations

    Abstract

    Hidden Markov trees in the wavelet domain are capable of accurately modeling the statistical behavior of real world signals by exploiting relationships between coefficients in different scales. The model is used to interpolate images by predicting coefficients at finer scales. Various optimizations and post-processing steps are also investigated to determine their effect on the performance of the interpolation. The interpolation algorithm was found to produce noticeably sharper images with PSNR values which outperform many other interpolation techniques on a variety of images.

    Original languageEnglish
    Pages (from-to)1957-1960
    Number of pages4
    JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume3
    StatePublished - 2001
    Event2001 IEEE International Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States
    Duration: 7 May 200111 May 2001

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