PROJECT TITLE :
Rgb-Nir Imaging With Exposure Bracketing For Joint Denoising And Deblurring Of Low-Light Color Images - 2017
Color pictures taken in low light-weight scenes are deteriorated with noise and motion blur. The simultaneous reduction of noise and motion blur from the low-light color pictures is difficult as a result of the imposed noise hinders accurate motion blur kernel estimation. To beat this problem, we build a novel imaging system using a single sensor that captures red, inexperienced, blue (RGB) and close to-infrared (NIR) pictures. Our imaging system captures low-light scenes with exposure bracketing, which may be a technique to acquire multiple pictures with different exposure times. It therefore permits us to obtain the short- and long-exposure RGB/NIR images. Both the short- and long-exposure NIR images taken using an NIR flash unit will be captured with less noise; therefore they allow estimation of motion blur kernel accurately. Primarily based on this reality, we perform joint denoising and deblurring of the low-light color image with the estimated motion blur kernel. Our experiments using real raw information captured by our imaging system demonstrate the effectiveness of our methodology.
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