Image interpolation using wavelet based hidden Markov trees

Author

Kinebuchi, Kentaro ; Muresan, D. Darian ; Parks, Thomas W.

Author_Institution

Sch. of Electr. & Comput. Eng., Cornell Univ., Ithaca, NY, USA

Volume

3

fYear

2001

fDate

2001

Firstpage

1957

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

Keywords

Markov processes; image processing; interpolation; optimisation; trees (mathematics); wavelet transforms; PSNR; image interpolation; interpolation algorithm; optimization; post-processing; real world signals; statistical behavior; wavelet based hidden Markov trees; wavelet based interpolation methods; wavelet coefficients; Filter bank; Hidden Markov models; Image reconstruction; Image resolution; Interpolation; Low pass filters; Predictive models; Probability distribution; Signal resolution; Wavelet domain;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on

Conference_Location

Salt Lake City, UT

ISSN

1520-6149

Print_ISBN

0-7803-7041-4

Type

conf

DOI

10.1109/ICASSP.2001.941330

Filename

941330