Image sequence processing using spatiotemporal segmentation

Author

Wu, Gene K. ; Reed, Todd R.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA

Volume

9

Issue

5

fYear

1999

fDate

8/1/1999 12:00:00 AM

Firstpage

798

Lastpage

807

Abstract

We investigate the improvements that can be obtained in several conventional video-processing algorithms through the incorporation of three-dimensional (3-D) (spatiotemporal) segmentation information. Four classes of image sequence processing techniques are considered: low-pass filtering, high-pass filtering, high-frequency emphasis, and 3-D Sobel filtering. It is demonstrated that segmentation information can improve the performance of these techniques substantially so that this approach may be promising for other applications (e.g., deinterlacing and resolution conversion) as well

Keywords

Markov processes; filtering theory; high-pass filters; image resolution; image segmentation; image sequences; low-pass filters; random processes; video signal processing; 3D Sobel filtering; 3D spatiotemporal segmentation; Gibbs-Markov random field model; contour relaxation; deinterlacing; high-frequency emphasis; high-pass filtering; image sequence processing; low-pass filtering; performance; region-growing method; resolution conversion; segmentation information; video-processing algorithms; Filtering; Image coding; Image converters; Image edge detection; Image processing; Image segmentation; Image sequence analysis; Image sequences; Low pass filters; Spatiotemporal phenomena;

fLanguage

English

Journal_Title

Circuits and Systems for Video Technology, IEEE Transactions on

Publisher

ieee

ISSN

1051-8215

Type

jour

DOI

10.1109/76.780367

Filename

780367