Shrinking Images for Efficient Transfer and Storage with Memristors

November 16, 2020

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,  Dr. Mahmoud Al-Qutayri, Professor, all from the System on Chip Center 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’s devices are “jam-packed with a variety of sensors, which are collectively expected to generate more than 40 zettabytes in 2020.” That’s one billion terabytes of data or one trillion gigabytes.

“This huge amount of generated data needs to be processed at a fast rate using complex algorithms to interpret the information,” explained Dr. Halawani. “This 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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