基于子空间优化的l^2-总变分图像恢复  

l^2-total variation image restoration based on subspace optimization

作　　者：刘晓光[1] 高兴宝[1] 周冬梅 

机构地区：[1]陕西师范大学数学与信息科学学院,西安710062 [2]成都高新新源学校,成都610041

出　　处：《计算机应用》2013年第4期1112-1114,共3页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61273311;61173094);中央高校基本科研业务费专项基金资助项目(GK201001002)

摘　　要：交替方向法被广泛用来求解总变分图像恢复问题,鉴于其搜索方向的不精确性对算法效率和图像恢复质量有着一定影响,提出了一种矫正方法。该方法以子空间优化为基础,结合能量函数泰勒展式及可微函数性质,利用先前搜索方向对当前方向进行有效矫正,提高了搜索方向的精确性。数值实验利用算法运行时间和峰值性噪比分别说明了该修正方法的效率和图像恢复质量。The alternating direction method is used widely to deal with the problem of total variation image restoration.A correction method was proposed to solve the problem of inaccuracy in search direction of the alternating direction method,which may influence the efficiency of the algorithm and the quality of the restored images adversely.Combining Taylor expansion of energy function and properties of differentiable function,this subspace-optimization-based method corrected the current direction effectively by utilizing the previous one,and improved the accuracy of search direction.The numerical experiments expound the efficiency of this algorithm and the quality of the restored images by running time and Peak-Signal-to-Noise Ratio（PSNR）,respectively.

关 键 词：整齐边界 总变分 交替方向法 子空间优化 图像恢复 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]