【摘要】 针对当前车用带钢表面图像信息修复所用时间较长,修复效果较差的问题,提出基于稀疏表示的车用带钢表面图像信息修复方法.根据像元点之间在车用带钢表面图像中存在的空间相关信息,结合像元点的灰度分布信息,采用二维直方图建立离散测度矩阵,获得车用带钢表面图像中需要修复的目标区域和背景区域.在稀疏表示原理的基础上构建稀疏修复模型,在车用带钢表面图像的目标区域和背景区域中对受损区域进行修复,能够有效获取车用带钢表面缺陷图像信息,实现车用带钢表面图像信息的修复.实验结果表明,所提方法对车用带钢表面图像信息修复的峰值信噪比较高、均方根误差较小,表明该方法的信息修复效果较好,且修复耗时较短,修复效率高.更多还原

【Abstract】 Aiming at the problems of a long time and poor repair effect of the current surface image information restoration of automotive strip steel,a method for repairing automotive strip surface image information based on sparse representation is proposed. According to the spatial correlation information existing between the pixel points in the au-tomotive strip surface image,combined with the gray distribution information of the pixel points,the two-dimensional histogram is used to establish the dispersion measure matrix,and the target area and background area needed to be repaired in the surface image of the automotive strip steel are obtained. The sparse repair model is constructed based on the sparse representation principle,and the damaged area is repaired in the target area and background area of the automotive strip surface image,which can effectively obtain the image information of the automotive strip surface defect and realize the automotive strip repair of surface image information. The experimental results show that the proposed method has a high peak signal-to-noise ratio and small root mean square error for the image information restoration of the automotive strip steel surface,indicating that the method has a better information restoration effect,the restoration time is shorter,and the restoration efficiency is higher.更多还原