The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-1/W5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 681–688, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-681-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 681–688, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-681-2015

  11 Dec 2015

11 Dec 2015

DEVELOPMENT OF NEUROMORPHIC SIFT OPERATOR WITH APPLICATION TO HIGH SPEED IMAGE MATCHING

M. Shankayi1, M. Saadatseresht1, and M. A. V. Bitetto2 M. Shankayi et al.
  • 1University of Tehran, Geomatics Engineering Faculty, Tehran, Iran
  • 2Institute of Cybernetics Research, Inc. , Robotics and Control Systems Department, New York, USA

Keywords: Neuromorphics, SIFT, Image Matching, FPGA, Neural Network

Abstract. There was always a speed/accuracy challenge in photogrammetric mapping process, including feature detection and matching. Most of the researches have improved algorithm's speed with simplifications or software modifications which increase the accuracy of the image matching process. This research tries to improve speed without enhancing the accuracy of the same algorithm using Neuromorphic techniques. In this research we have developed a general design of a Neuromorphic ASIC to handle algorithms such as SIFT. We also have investigated neural assignment in each step of the SIFT algorithm. With a rough estimation based on delay of the used elements including MAC and comparator, we have estimated the resulting chip's performance for 3 scenarios, Full HD movie (Videogrammetry), 24 MP (UAV photogrammetry), and 88 MP image sequence. Our estimations led to approximate 3000 fps for Full HD movie, 250 fps for 24 MP image sequence and 68 fps for 88MP Ultracam image sequence which can be a huge improvement for current photogrammetric processing systems. We also estimated the power consumption of less than10 watts which is not comparable to current workflows.