Rgb-Nir Imaging With Exposure Bracketing For Joint Denoising And Deblurring Of Low-Light Color Images - 2017 PROJECT TITLE :Rgb-Nir Imaging With Exposure Bracketing For Joint Denoising And Deblurring Of Low-Light Color Images - 2017ABSTRACT: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. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Image Denoising Via Collaborative Support-Agnostic Recovery - 2017 Inverse Sparse Group Lasso Model For Robust Object Tracking - 2017
