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- W4308396317 abstract "Abstract The history of computing started with analog computers consisting of physical devices performing specialized functions such as predicting the position of astronomical bodies and the trajectory of cannon balls. In modern times, this idea has been extended, for example, to ultrafast nonlinear optics serving as a surrogate analog computer to probe the behavior of complex phenomena such as rogue waves. Here we discuss a new paradigm where physical phenomena coded as an algorithm perform computational imaging tasks. Specifically, diffraction followed by coherent detection becomes an image enhancement tool. Vision Enhancement via Virtual diffraction and coherent Detection (VEViD) reimagines a digital image as a spatially varying metaphoric “lightfield” and then subjects the field to the physical processes akin to diffraction and coherent detection. The term “Virtual” captures the deviation from the physical world. The light field is pixelated and the propagation imparts a phase with dependence on frequency which is different from the monotonically-increasing behavior of physical diffraction. Temporal frequencies exist in three bands corresponding to the RGB color channels of a digital image. The phase of the output, not the intensity, represents the output image. VEViD is a high-performance low-light-level and color enhancement tool that emerges from this paradigm. The algorithm is extremely fast, interpretable, and reduces to a compact and intuitively-appealing mathematical expression. We demonstrate image enhancement of 4k video at over 200 frames per second and show the utility of this physical algorithm in improving the accuracy of object detection in low-light conditions by neural networks. The application of VEViD to color enhancement is also demonstrated." @default.
- W4308396317 created "2022-11-11" @default.
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- W4308396317 date "2022-11-08" @default.
- W4308396317 modified "2023-09-25" @default.
- W4308396317 title "VEViD: Vision Enhancement via Virtual diffraction and coherent Detection" @default.
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- W4308396317 doi "https://doi.org/10.1186/s43593-022-00034-y" @default.
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