A NURBS-based error concealment technique for corrupted images from packet loss

An error concealment using non-uniform rational B-spline (NURBS) is proposed. NURBS has been employed by many CAD/CAM systems as a fundamental geometry representation. Despite the fact that NURBS has gained tremendous popularity from the CAD/CAM and computer graphics community, its application on exploring the image problem only received little attention. On the other hand, the image contents might be corrupted or lost during transmission. Although there are quite a few existing techniques, yet developing an effective approach to conceal the error remains as one of the hottest research topics. Thus the aim of this study is to develop an image reconstruction technique using NURBS. The key idea is to use NURBS to represent the portion of image data without corruption. By accomplishing this, a single-hidden layer neural network is employed to learn the appropriate control points of NURBS. After learning, NURBS is then used to render the corrupted image data. Experimental results indicate that the proposed approach exhibits promising performance.