Abstract
Wavelet transform provides excellent energy compaction and exploits redundancy for better image compression. This paper analyses the performance of wavelet-based image compression techniques, namely set partitioning in hierarchical trees (SPIHT), set partitioned embedded block (SPECK) and JPEG2000. Image quality measured as peak signal-to-noise ratio and computational complexity, i.e. encoding and decoding times, is calculated for these techniques. Simulation results show that JPEG2000 outperforms other state-of-the-art wavelet image codecs (SPIHT and SPECK) in coding efficiency and computational complexity. Simulation is carried out on various images of different dimensions at different bit rates using MATLAB software.
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Bano, N., Alam, M., Ahmad, S. (2018). Performance Evaluation of Wavelet-Based Image Compression Techniques. In: Singh, R., Choudhury, S., Gehlot, A. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 624. Springer, Singapore. https://doi.org/10.1007/978-981-10-5903-2_79
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DOI: https://doi.org/10.1007/978-981-10-5903-2_79
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