Low-Light Color Image Super-Resolution Using RGB/NIR Sensor

• Published in: 2018 25th IEEE International Conference on Image Processing (ICIP) pp. 56 - 60
• Main Authors: Honda, Takayuki, Hamamoto, Takayuki, Sugimura, Daisuke
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-10-2018
• Subjects: Color; Image color analysis; Image reconstruction; Imaging; Low-light scene; Multi-frame super-resoluton; Noise reduction; RGB/NIR single sensor; Spatial resolution
• ISSN: 2381-8549
• DOI: 10.1109/ICIP.2018.8451274

We propose a method for super-resolution (SR) of low-resolution (LR) color images taken in low-light scenes. Our method is based on multi-frame SR technique, which fuses multiple LR images taken at different camera positions to synthesize a high-resolution color image. Previous methods have implicitly assumed that LR images could be captured with less noise and blur. However, heavy noise and motion blur will be imposed on images taken in low-light scene. They make it difficult to super-resolve low-light images with high quality. To overcome this problems, we utilize a single sensor that captures red, green, blue (RGB) and near-infrared (NIR) information. Since NIR images taken using an NIR flash unit can be captured with less noise, they contribute to effective reduction of image artifacts in super-resolving LR images. Using multiple RGB/NIR raw images, we jointly perform deblurring, denoising and SR of LR images. Experiments using real raw data demonstrate the effectiveness of our method.