Abstract
In this Paper we propose a highly scalable image compression scheme based on the set partitioning in hierarchical trees (SPIHT) algorithm. Our algorithm called highly scalable SPIHT (HS-SPIHT), supports spatial and SNR scalability and provides a bit stream that can be easily adapted (reordered) to given bandwidth and resolution requirements by a simple transcoder (parser). The HS-SPIHT algorithm adds the spatial scalability feature without sacrificing the SNR embeddedness property as found in the original SPIHT bit stream. HS-SPIHT finds applications in progressive Web browsing, flexible image storage and retrieval, and image transmission over heterogeneous networks. Here we have written the core processor Microblaze is designed in VHDL (VHSIC hardware description language), implemented using XILINX ISE 8.1 Design suite the algorithm is written in system C Language and tested in SPARTAN-3 FPGA kit by interfacing a test circuit with the PC using the RS232 cable. The test results are seen to be satisfactory. The area taken and the speed of the algorithm are also evaluated.
Highlights
One of the major challenges in enabling mobile multimedia data services will be the need to process and wirelessly transmit a very large volume of data
If multiple interrupts are needed, an interrupt controller must be used to handle multiple interrupt requests to MicroBlaze shown in figure l0.An interrupt controller is available for use with the Xilinx Embedded Development Kit (EDK) software tools
EDK includes a variety of tools and applications to assist the designer to develop an embedded system right from the hardware creation to final implementation of the system on an Field Programmable Gate Arrays (FPGAs)
Summary
One of the major challenges in enabling mobile multimedia data services will be the need to process and wirelessly transmit a very large volume of data. One approach to mitigate to this problem is to reduce the volume of multimedia data transmitted over the wireless channel via data compression techniques. This has motivated active research on multimedia data compression techniques such as JPEG [1,2], JPEG 2000 [2] and MPEG [3]. These approaches concentrate on achieving higher compression ratio without sacrificing the quality of the image. All schemes above are used or two-dimensional data (images) and while they are excellent for images they might not be that well suited for compression of three-dimensional data such as image stacks
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