Multi-Frame Low-Light Signal-to-Noise Enhancement and Super Resolution

Problem: Thermal images typically appear grainy and ill-defined Technology: This invention proposes an image-processing algorithm that recovers information from extremely noisy, low-light video and creates a super-resolution image. The program combines a series of low-resolution images intelligently by identifying their positions inside high-resolution reference images. The resolution of digital images is enhanced by moving the camera (dither-type) and estimating the point-spread function (PSF) from the motion. The PSF is conventionally assumed to be Gaussian and is applied to the image to reduce noise, but the Gaussian estimate is very uncertain. This is a much more robust approach and does not require calibration of the imaging system. Christopher Noble crn@mit.edu

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