Shrinking Images for Efficient Transfer and Storage with Memristors
A team of researchers from Khalifa University has investigated a memristor-based image compression architecture to speed up image compression while also making the devices using this technology much smaller and more energy efficient.
The team comprised Dr. Yasmin Halawani, Post-doctoral Researcher, Dr. Baker Mohammad, Associate Professor,聽 Dr. Mahmoud Al-Qutayri, Professor, all from the System-on-Chip Lab and Department of Electrical and Computer Engineering at Khalifa University, and Dr. Said Al-Sarawi from the Center for Biomedical Engineering at the University of Adelaide, Australia.
Dr. Halawani explained in her doctoral thesis that today鈥檚 devices are 鈥渏am-packed with a variety of sensors, which are collectively expected to generate more than 40 zettabytes in 2020.鈥� That鈥檚 one billion terabytes of data or one trillion gigabytes.
鈥淭his huge amount of generated data needs to be processed at a fast rate using complex algorithms to interpret the information,鈥� explained Dr. Halawani. 鈥淭his is computationally demanding, but Internet-of-Things devices tend to be energy-constrained and have limited resources, so innovative architectures and technologies that enable efficient.
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