Fast fractal image compression algorithm based image interfacing system

Buoys are floating devices, used to capture various parameters of the ocean environments through different mechanisms. The modular architecture of the buoys is highly dynamic depending on the type of buoys. This work focuses on the interfacing system between the image acquisition and transmission modules of data buoys. The major requirement between the image acquisition and the transmission process is a good compression of the captured image. Also, to enhance the compatibility of the transmission process with available satellite resources the compression ratio has to be highly increased to match with the standards of satellite communication. Existing conventional compression algorithms like Joint Picture Expert Group (JPEG), Set Partition In Hierarchical Trees (SPIHT) etc., failed to give the required compression ratio. This work aims to develop an efficient low power, high compression image interfacing system. The developed system captures the image and compresses it in such a way that the compressed output image becomes compatible for satellite communication. The major contribution of this work is the design and implementation of Fast Fractal Image Compression Algorithm which is based on Iterated Function System (IFS) to achieve the expected high compression ratio. The results obtained ensure the feasibility of high compression ratio. Future work aims to embed the fast fractal algorithm in the Blackfin processor ADSP BF-527.