Multiresolution image compression with BSP trees and multilevel BTC

Author

Rabiee, Hamid R. ; Kashyap, R.L. ; Radha, H.

Author_Institution

Dept. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA

Volume

3

fYear

1995

fDate

23-26 Oct 1995

Firstpage

600

Abstract

This paper presents a new multiresolution segmentation-based algorithm for image compression. High quality low bit rate image compression is achieved by recursively coding the binary space partitioning (BSP) tree representation of images with multilevel block truncation coding (BTC). Comparison with JPEG at rates below 0.25 bit/pixel shows superior performance both in terms of power signal-to-noise ratio (PSNR) and subjective image quality

Keywords

block codes; data compression; image coding; image representation; image resolution; image segmentation; tree data structures; BSP trees; binary space partitioning tree representation; hgh quality low bit rate image compression; multilevel BTC; multilevel block truncation coding; multiresolution segmentation-based algorithm; performance; power signal-to-noise ratio; recursive coding; segmentation-based algorithm; subjective image quality; Bit rate; Image coding; Image resolution; Image segmentation; PSNR; Partitioning algorithms; Pixel; Signal resolution; Signal to noise ratio; Transform coding;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1995. Proceedings., International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-7310-9

Type

conf

DOI

10.1109/ICIP.1995.537706

Filename

537706