RGB-NIR imaging with exposure bracketing for joint denoising and deblurring of low-light color images

• Main Authors: Yamashita, Hiroki, Sugimura, Daisuke, Hamamoto, Takayuki
• Format: Conference Proceeding
• Language: English
• Subjects: Color; deblurring; denoising; Estimation; exposure bracketing; Image reconstruction; Image restoration; Imaging; Kernel; low-light image restoration; Noise reduction; RGB/NIR single sensor
• ISSN: 2379-190X
• DOI: 10.1109/ICASSP.2017.7953319

Color images taken in low light scenes are deteriorated with noise and motion blur. The simultaneous reduction of noise and motion blur from the low-light color images is difficult because the imposed noise hinders accurate motion blur kernel estimation. To overcome this problem, we build a novel imaging system using a single sensor that captures red, green, blue (RGB) and near-infrared (NIR) images. Our imaging system captures low-light scenes with exposure bracketing, which is a technique to acquire multiple images with different exposure times. It thus allows 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 can be captured with less noise; thus they enable estimation of motion blur kernel accurately. Based on this fact, we perform joint denoising and deblurring of the low-light color image with the estimated motion blur kernel. Our experiments using real raw data captured by our imaging system demonstrate the effectiveness of our method.