High-Resolution, Lightweight Remote Sensing via Harmonic Diffractive Optical Imaging Systems and Deep Denoiser Prior Image Restoration
Shuo Zhong, Xijun Zhao, Dun Liu, Haibing Su, Zongliang Xie, Bin Fan · IEEE Transactions on Geoscience and Remote Sensing · 2024
The weight of traditional space optical imaging systems often increases nearly cubically with the increase in aperture size. To overcome this limitation, this study proposes the use of a lightweight harmonic diffractive optical imaging system combined with deep denoiser prior image restoration, to achieve high-resolution, lightweight remote sensing.This research first designed a novel 150-order harmonic diffractive optical element (H-DOE) featuring a 40-mm aperture size and a 320-mm focal length, which is equipped with seven annular zones covering a broad spectral band (500-800 nm). Its slim structure significantly reduces weight and volume, thereby lowering its launch costs. Furthermore, to address the blurring issues encountered in H-DOE imaging tasks and attain enhanced image resolution, this study incorporates an advanced image restoration technique. This technique employs a deep denoiser as a prior module, which is embedded into a model-based image restoration optimization framework. The newly trained deep denoiser utilizes a U-Net architecture integrating a transformer and residual structures and is adept at handling complex noise during the optical imaging process. Experimental results demonstrate that the performance of the proposed image restoration strategy based on a deep denoiser surpasses that of the existing technologies, elevating the resolvable frequency of the modulation transfer function (MTF) of an H-DOE imaging system from 40.58 lp/mm to 98.55 lp/mm, an enhancement of 142.9%. This significant image quality improvement showcases its vast potential for use in future high-resolution, lightweight remote sensing applications.