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Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

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Thermal noise analysis of near-sensor image processing

Description
Commonly, image processing is handled on a CPU that is connected to the image sensor by a wire. In these far-sensor processing architectures, there is energy loss associated with sending data across an interconnect from the sensor to the CPU. In an effort to increase energy efficiency, near-sensor processing architectures…

Commonly, image processing is handled on a CPU that is connected to the image sensor by a wire. In these far-sensor processing architectures, there is energy loss associated with sending data across an interconnect from the sensor to the CPU. In an effort to increase energy efficiency, near-sensor processing architectures have been developed, in which the sensor and processor are stacked directly on top of each other. This reduces energy loss associated with sending data off-sensor. However, processing near the image sensor causes the sensor to heat up. Reports of thermal noise in near-sensor processing architectures motivated us to study how temperature affects image quality on a commercial image sensor and how thermal noise affects computer vision task accuracy. We analyzed image noise across nine different temperatures and three sensor configurations to determine how image noise responds to an increase in temperature. Ultimately, our team used this information, along with transient analysis of a stacked image sensor’s thermal behavior, to advise thermal management strategies that leverage the benefits of near-sensor processing and prevent accuracy loss at problematic temperatures.
ContributorsJones, Britton Steele (Author) / LiKamWa, Robert (Thesis director) / Jayasuriya, Suren (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12