The task of low-light image enhancement, in which the quality of images captured in low illumination conditions is enhanced, has high importance within industrial, security and scientific applications. In this paper we discuss Vision Enhancement via Virtual diffraction and coherent Detection (VEViD), a novel physics-inspired algorithm in which we map the physics of diffractive optics and phase detection to that of digital image processing. By applying virtual diffraction, we create a nontrivial spatial phase profile that encodes an enhanced version of the incoming image, a version in which the image’s previously unseen low-light details are made accessible to human and computer perception.
In this talk, we will present PhyCV: the first physics-inspired computer vision library. PhyCV is a new class of computer vision algorithms directly derived from the equations of physics governing physical phenomena. The algorithms appearing in the first release emulate, in a metaphoric sense, the propagation of light through a physical medium with natural and engineered diffractive properties followed by coherent detection.
This talk will present a science-as-a-service application that will provide public access to a new family of computational imaging algorithms that are inspired by optical physics. These algorithms are emerging as the best-in-class tools for certain digital image processing functions such as edge and texture detection, and more. A cloud application developed in collaboration with and hosted by AWS, the application features various tools, sample data, and workflows. The cloud approach provides data security, a crucial issue in the biomedical industry and exposes the broader biomedical community to the ongoing innovations in algorithms.
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