SAR self-enhanced by electro-optical network (SARSEEN)

Kenneth Tran; Wesam Sakla; Hamid Krim

doi:10.1117/12.2618829

8 June 2022 SAR self-enhanced by electro-optical network (SARSEEN)

Kenneth Tran, Wesam Sakla, Hamid Krim

Proceedings Volume 12122, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI; 121220V (2022) https://doi.org/10.1117/12.2618829
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

We investigate the relationship between paired SAR and optical images. SAR sensors have the capabilities of penetrating clouds and capturing data at night, whereas optical sensors cannot. We are interested in the case where we have access to both modalities during training, but only the SAR during test time. To that end, we developed a framework that inputs a SAR image and predicts a Canny edge map of the optical image, which retains structural information, while removing superfluous details. Our experiments show that by additionally using this predicted edge map for downstream tasks, we can outperform the same model that only uses the SAR image.

Citation Download Citation

Kenneth Tran, Wesam Sakla, and Hamid Krim "SAR self-enhanced by electro-optical network (SARSEEN)", Proc. SPIE 12122, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI, 121220V (8 June 2022); https://doi.org/10.1117/12.2618829

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