Stripe and random noise are two different degradation phenomena that commonly coexist in
optical remote sensing images, and they are often modeled as inverse problems. In model …

Early fault diagnosis of rotating machinery is crucial in the industry. The network parameters
of the traditional deep learning-based fault diagnosis method are optimized only by the …

Stripe noise from different remote sensing imaging systems varies considerably in terms of
response, length, angle, and periodicity. Due to the complex distributions of different stripes …

Hyperspectral unmixing has attracted much attention in recent years. Single sparse
unmixing assumes that a pixel in a hyperspectral image consists of a relatively small number …

Cloud and cloud shadow (cloud/shadow) removal from multitemporal satellite images is a
challenging task and has elicited much attention for subsequent information extraction …

Limited by the imaging paradigm, stripes are pervasive in remote sensing scenes, and its
intensity, density, and periodicity differ dramatically among different imaging systems …