Title:  Energy-efficient Image Processing for Intelligent Sensor Systems

Committee:

Dr. Mukhopadhyay, ECE, Advisor

Dr. Raychowdhury, ECE, Chair

Dr. Yalamanchili, ECE

Abstract:

The objective of the proposed research is to design energy-efficient image processing algorithms and architecture for intelligent wireless image sensor systems. For reliable delivery of region-of-interest (ROI) under dynamic environment, the research explores low-power moving object detection with enhanced noise robustness. Based on the ROI information, the system energy is further optimized by a low-power ROI-based coding scheme and an on-line data rate controller. To enable machine learning based intelligent image processing with limited hardware resources, the research proposes neural network design with lower storage and computation demand. The storage demand is reduced by compressing the neural network weights with an adaptive image encoding algorithm. The computation demand of convolutional neural networks is optimized by mapping the entire network parameters and operations into the frequency domain. FPGA verification and analysis of on-chip neural network inference will complete this research, enabling intelligent image processing on resource-constrained mobile sensor platforms.