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Spectral unmixing is to decompose the hyperspectral data into endmembers and abundances. It has been known to be a challenging and ill-posed task due to the corruption of noise as well as complex environmental conditions. In this paper, we propose a part-based denoising autoencoder with unique structure that solves the unmixing challenges. The effective l21 norm and denoising constraints are applied...
Pansharpening refers to the fusion of a high spatial resolution panchromatic image with high spectral resolution multispectral or hyperspectral images (MSI or HSI) to yield high resolution data in both spectral and spatial domains. It has been widely adopted as a primary preprocessing step for numerous applications. In this paper, we perform a literature survey of various pansharpening algorithms...
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