Sphit

Page 1 of 38

Sphit

By | Jan. 2013
Page 1 of 38
HIGHLY SCALABLE IMAGE COMPRESSION BASED ON SPIHT FOR NETWORK APPLICATIONS
Habibollah Danyali and Alfred Mertins
School of Electrical, Computer and Telecommunications Engineering University of Wollongong, Wollongong, NSW 2522, Australia
Email: hd04, mertins @uow.edu.au
 

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In general, an level wavelet decomposition allows at most
levels of spatial resolution. To distinguish between different resolution levels, we denote the lowest spatial resolution level as level . The full image then becomes resolution level 1. The three

subbands that need to be added to increase the resolution from level to level
are referred to as level
resolution subbands (see Fig. 1). An algorithm that provides full spatial scalability would encode the different resolution levels separately, allowing a transcoder or the decoder to directly access the data needed to reconstruct with a desired spatial resolution. The original SPIHT algorithm, however, encodes the entire wavelet tree in a bitplane by bitplane manner and produces a bitstream that contains the information about the different spatial resolutions in no particular order.

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0-7803-7622-6/02/$17.00 ©2002 IEEE

2. HIGHLY SCALABLE SPIHT (HS-SPIHT)
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Traditional image coding systems have only focused on efficient compression of image data. The main objective of such systems is optimizing image quality at given bit rate. Due to the explosive growth of the Internet and networking technology, nowadays a huge number of users with different capabilities of processing and network access bandwidth can transfer and access data easily. For transmission of visual data on such a heterogenous network, efficient compression itself is not sufficient. There is an increasing demand for scalability to optimally service each user according to his bandwidth and computing capabilities. A scalable image coder generates a bitstream which consists of a set of embedded parts that...