基于双树复小波的图像修复

小波变换技术已被广泛应用于图像修复领域,但其在图像修复过程中出现的边缘部分模糊或不连接的情况成为了一个难点。针对此问题,提出了基于双树复小波变换的图像修复算法。该算法使用双树复小波变换对破损图像进行多尺度和多方向的分解,对各个高频方向子带使用全变分(Total Variation,TV)模型进行快速修复,各个低频分量使用改进了的曲率驱动扩散(Curvature-Driven-Diffusions,CCD)模型进行迭代修复,最后通过小波逆变换得到最终的修复图像。实验结果表明,该方法很好地推广了双树复小波变换在图像修复领域中的应用,并且在图像纹理的修复以及在结构部分的填充都有较好的效果。

Image Inpainting Based on Dual-tree Complex Wavelet Transform

The wavelet transform technology has been widely used in the field of digital image inpainting,however,the image inpainting based on wavelet transform will appear the phenomenon of edge fuzzy and not connection,which becomes a difficult problem.Based on the multiscale and multidirectional decomposition and the traditional method of ima-ge inpainting,a new algorithm of image inpainting based on dual-tree complex wavelet transform was proposed.Firstly,the image is decomposed into low frequency and high frequency parts by using the dual-tree complex wavelet transform.Then the parts of different frequency after image decomposition are inpainted respectively.The high frequency components of the image are inpainted by the total variation model,and an improved curvature-driven-diffusion is used to repair the low frequency components.Finally,the final image is obtained by dual-tree complex wavelet transform reconstruction process.The experimental results show that the proposed algorithm is very good for the promotion of the dual-tree complex wavelet transform in image inpainting application and gets better repair both in the part of texture and the part of structure.