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MULTI-APERTURE IMAGE PROCESSING USING DEEP LEARNING
GEONHO HWANG,CHANG HOON SONG,TAE KYUNG LEE,HOJUN NA,MYUNGJOO KANG 한국산업응용수학회 2023 Journal of the Korean Society for Industrial and A Vol.27 No.1
In order to obtain practical and high-quality satellite images containing high- frequency components, a large aperture optical system is required, which has a limitation in that it greatly increases the payload weight. As an attempt to overcome the problem, many multi-aperture optical systems have been proposed, but in many cases, these optical systems do not include high-frequency components in all directions, and making such an high-quality image is an ill-posed problem. In this paper, we use deep learning to overcome the limitation. A deep learning model receives low-quality images as input, estimates the Point Spread Function, PSF, and combines them to output a single high-quality image. We model images obtained from three rectangular apertures arranged in a regular polygon shape. We also propose the Modula- tion Transfer Function Loss, MTF Loss, which can capture the high-frequency components of the images. We present qualitative and quantitative results obtained through experiments.
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