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Heterogeneous Change Detection With Hyperspectral Prisma Data And Sar Cosmo-Skymed Imagery | IEEE Conference Publication | IEEE Xplore

Heterogeneous Change Detection With Hyperspectral Prisma Data And Sar Cosmo-Skymed Imagery


Abstract:

This paper proposes a novel approach for heterogeneous Change Detection (CD) between hyperspectral (HS) and polarimetric synthetic aperture radar (PolSAR) images. The met...Show More

Abstract:

This paper proposes a novel approach for heterogeneous Change Detection (CD) between hyperspectral (HS) and polarimetric synthetic aperture radar (PolSAR) images. The method utilizes an image-to-image (I2I) translation approach with cyclic generative networks to transfer data between the two domains. In this paper, we extend previous work where each image is transformed into the other domain by combining deep learning architectures and a formulation based on affinity matrices, thus resulting in two pairs of homogeneous images. Homogeneous CD algorithms are applied to both pairs, and the results are merged to generate a single change map. However, the disparity in the number of bands between HS and SAR data presents a challenge. To overcome this, a new method is introduced that combines dimensionality reduction with I2I translation and affinity matrix in a fully unsupervised manner. Experimental evaluation and comparative analysis with respect to a homogeneous CD method are presented.
Date of Conference: 16-21 July 2023
Date Added to IEEE Xplore: 20 October 2023
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Conference Location: Pasadena, CA, USA

References

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