Video Superresolution Reconstruction Using Iterative Back Projection with Critical-Point Filters Based Image Matching. (11th March 2015)

• Record Type: Journal Article
• Authors: Zhang, Yixiong; Tao, Mingliang; Yang, Kewei; Deng, Zhenmiao
• Other Names: Kotropoulos Constantine Academic Editor.
• Is Part Of: Advances in multimedia. Volume 2015(2015)
• Publication Date: 2015-03-11
• Subjects: Multimedia systems -- Periodicals; Computer networks -- Periodicals; Multimédia; Réseaux d'ordinateurs; Computer networks; Multimedia systems; Periodicals; 006.7
• DOI: 10.1155/2015/285969
• Languages: English
• ISSNs: 1687-5680

Abstract

Abstract : To improve the spatial resolution of reconstructed images/videos, this paper proposes a Superresolution (SR) reconstruction algorithm based on iterative back projection. In the proposed algorithm, image matching using critical-point filters (CPF) is employed to improve the accuracy of image registration. First, a sliding window is used to segment the video sequence. CPF based image matching is then performed between frames in the window to obtain pixel-level motion fields. Finally, high-resolution (HR) frames are reconstructed based on the motion fields using iterative back projection (IBP) algorithm. The CPF based registration algorithm can adapt to various types of motions in real video scenes. Experimental results demonstrate that, compared to optical flow based image matching with IBP algorithm, subjective quality improvement and an average PSNR score of 0.53 dB improvement are obtained by the proposed algorithm, when applied to video sequence.