Flexible, highly scalable, object-based wavelet image compression algorithm for network applications

H. Danyali*, A. Mertins

*Corresponding author for this work
24 Citations (Scopus)


The authors propose a highly scalable image compression scheme based on the set partitioning in hierarchical trees (SPIHT) algorithm. The proposed algorithm, called highly scalable SPIHT (HS-SPIHT), adds the spatial scalability feature to the SPIHT algorithm through the introduction of multiple resolution-dependent lists and a resolution-dependent sorting pass. It keeps the important features of the original SPIHT algorithm such as compression efficiency, full SNR scalability and low complexity. The flexible bitstream of the HS-SPIHT encoder can easily be adapted to various resolution requirements at any bit rate. The parsing process can be carried out on-the-fly without decoding the bitstream by a simple parser (transcoder) that forms a part of a smart network. The HS-SPIHT algorithm is further developed for fully scalable coding of arbitrarily shaped visual objects. The proposed highly scalable algorithm finds applications in progressive web browsing, visual databases and especially in image transmission over heterogeneous networks.

Original languageEnglish
JournalIEE Proceedings: Vision, Image and Signal Processing
Issue number6
Pages (from-to)498-510
Number of pages13
Publication statusPublished - 01.12.2004


Dive into the research topics of 'Flexible, highly scalable, object-based wavelet image compression algorithm for network applications'. Together they form a unique fingerprint.

Cite this