摘要
分析了基于TV模型的图像修复算法,针对各参考点梯度模值的大小不同,对原始模型进行了改进.该算法通过计算待修复区域像素点的梯度信息来构造一个扩散函数,利用其控制各参考点对待修复区域的贡献值,然后再进行加权处理.实验结果表明修复变化剧烈和有较大破损的图像效果较好,图像边缘清晰,过渡自然.
The image inpainting algorithm based on total variation model is analyzed. For the different size of the gradient value of each reference point, an improved image inpainting algorithm is proposed. The algorithm constructs a spread function by calculating the gradient information ofpixel, and then they are weighted. Spread function control the contribution of the reference point on the repair area. Experimental results show that this algorithm works better in repair of damaged images which changes dramatically and the region is larger. Also, the image sharp edges and the boundary transit naturally.
出处
《计算机系统应用》
2013年第3期121-124,58,共5页
Computer Systems & Applications
基金
国家自然科学基金(91120014)
关键词
图像修复
各向异性
TV算法
扩散函数
梯度信息
image inpainting
anisotropic
total variation
spread function
gradient information
