High-resolution reconstruction of objects from cloud-covered infrared images

Jing Wang; Jason F. Ralph; John Y. Goulermas

doi:10.1117/12.818511

11 May 2009 High-resolution reconstruction of objects from cloud-covered infrared images

Jing Wang, Jason F. Ralph, John Y. Goulermas

Proceedings Volume 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII; 733617 (2009) https://doi.org/10.1117/12.818511
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

FLIR images are essential for the detection and recognition of ground targets. Small targets can be enhanced using super-resolution techniques to improve the effective resolution of the target area using a sequence of low-resolution images. However, when there is significant cloud cover, several problems can arise: clouds can obscure a target (partially or fully), they can affect the accuracy of image registration algorithms, and they can reduce the contrast of the object against the background. To reconstruct an image in the presence of cloud cover, image correlation metrics from optical flow and a robust super-resolution algorithm have been used to compile a 'best' frame.

Citation Download Citation

Jing Wang, Jason F. Ralph, and John Y. Goulermas "High-resolution reconstruction of objects from cloud-covered infrared images", Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 733617 (11 May 2009); https://doi.org/10.1117/12.818511

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