摘要
This paper introduces a new method of converting interlaced video to a progressively scanned video and image, The new method is derived from Bayesian framework with the spatial-temporal smoothness constraint and the MAP is done by minimizing the energy functional, The half-quadratic regularization method is used to solve the corresponding partial differential equations （PDEs）, This approach gives the improved results over the conventional de-interlacing methods, Two criteria are proposed in the paper, and they can be used to evaluate the performance of the de-interlacing algorithms,
This paper introduces a new method of converting interlaced video to a progressively scanned video and image, The new method is derived from Bayesian framework with the spatial-temporal smoothness constraint and the MAP is done by minimizing the energy functional, The half-quadratic regularization method is used to solve the corresponding partial differential equations （PDEs）, This approach gives the improved results over the conventional de-interlacing methods, Two criteria are proposed in the paper, and they can be used to evaluate the performance of the de-interlacing algorithms,
作者
YIN XueMin1,2,3, YUAN JianHua1,2, LU XiaoPeng1,2 & ZOU MouYan1,2 1 Institute of Electronics, Chinese Academy of Sciences, Beijing 100080, China
2 Graduate School, Chinese Academy of Sciences, Beijing 100039, China
3 Jiuquan Satellite Launch Center, Lanzhou 732750, China
