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Strong scattering medium brings great difficulties to optical imaging, whichis also a problem in medical imaging and many other fields. Optical memoryeffect makes it possible to image through strong random scattering medium.However, this method also has the limitation of limited angle field-of-view(FOV), which prevents it from being applied in practice. In this paper, a kindof practical convolutional neural network called PDSNet is proposed, whicheffectively breaks through the limitation of optical memory effect on FOV.Experiments is conducted to prove that the scattered pattern can bereconstructed accurately in real-time by PDSNet, and it is widely applicable toretrieve complex objects of random scales and different scattering media.

Learning-based real-time method to looking through scattering medium beyond the memory effect