Real-Time Document Image Super-Resolution by Fast Matting
Yun Ping Zheng, Xudong Kang, Shutao Li, Yuan He, Jun Sun · 2014
From a single low resolution image, a real-time document image super-resolution algorithm is proposed to obtain high resolution document image with sharp text boundaries. First, a highly efficient document image matting algorithm based on local linear modeling is designed to decompose the input image into text, foreground and background layers, which contain the text edge information, the color information of the foreground and background respectively. Then the text layer is up-sampled with Teager filter to increase the sharpness of the text. For efficiency, the foreground and background layers are simply up-sampled through the bi-cubic interpolation. Finally, these three high resolution layers are composed to obtain the high-resolution image. Experiments on real scanned document images demonstrate the effectiveness of the proposed method in both visual perception and OCR performance