Rate My Professor Scott Budge

Budge's research specializations encompass LADAR signal processing, texel camera calibration and registration for fused LiDAR and digital imagery, image and data compression via vector quantization and wavelet-based methods, real-time digital signal processing, multispectral image registration, and people counting and tracking using sensor data. Key publications include "Obstacle detection using range-difference events" (Optical Engineering, 2022, with C.B. Cornwall), "Method for 3-D scene reconstruction using fused LiDAR and imagery from a texel camera" (IEEE Transactions on Geoscience and Remote Sensing, 2019, with T.C. Bybee), "Dynamic visualization of three-dimensional images from multiple texel images created from fused ladar/digital imagery" (Optical Engineering, 2017, with C.C. Killpack), "Automatic registration of fused lidar/digital imagery (texel images) for three-dimensional image creation" (Optical Engineering, 2015, with N.S. Badamikar and X. Xie), and earlier contributions such as "Classification using set-valued Kalman filtering and Levi's decision theory" (IEEE Transactions on Systems, Man, and Cybernetics, 1994, with T.K. Moon). He has mentored over 15 graduate students to completion. Awards include Outstanding Teacher of the Year (Department of Electrical and Computer Engineering, 2012), Undergraduate Research Mentor of the Year (2009), Outstanding Researcher of the Year (1997), Faculty Service Awards (2022, department and College of Engineering), IEEE Senior Member elevation (2000), and a Certificate of Appreciation from Pacific Northwest National Laboratory (2003).