With the development of a myriad of imaging sensors and associated image processing algorithms to address the DVE problem relative performance evaluations have becoming increasingly important. In this paper, we introduce image quality metrics which have been selected for DVE applications. These quality metrics are based on the human visual system and consider factors such as induced processing noise, information content, and preserved image detail. These measures are shown to be useful for the evaluation of imaging sensors and associated processing. In addition, these measures provide direction for tuning and optimizing DVE local area processing (LAP) algorithms. Results will be shown for sample test images and dust trials of a camera with various image processing algorithms.

Date Published: 5 May 2017
PDF: 7 pages
Proc. SPIE 10197, Degraded Environments: Sensing, Processing, and Display 2017, 101970E (5 May 2017); doi: 10.1117/12.2262576

Published in SPIE Proceedings Vol. 10197:
Degraded Environments: Sensing, Processing, and Display 2017
John (Jack) N. Sanders-Reed; Jarvis (Trey) J. Arthur III, Editor(s)