Exemplar Based Image Inpainting Algorithm Using Direction Features of Curvelet Transform
LI Zhi-dan1, HE Hong-jie1, YIN Zhong-ke2, CHEN Fan1
1. Sichuan Key Laboratory of Signal and Information Processing, Southwest Jiaotong University, Chengdu, Sichuan 610031, China;
2. Institute of Remote Sensing Information, Beijing 100192, China
Whether the structure coherence and neighborhood consistency can be well maintained directly determines the performance of an inpainting algorithm.To achieve a better inpainting performance, this paper proposes an exemplar based image inpainting algorithm based on direction features extracted by Curvelet transform.Firstly, the super-wavelet transform is applied to extract four direction features of the corrupted image.Then the color and direction information are utilized to measure the similarities between patches.Subsequently, a color-direction structure sparsity function is defined.Afterwards, multiple suitable candidate patches are searched based on the weighted color-direction distance and these candidate patches are applied to sparsely represent target patch under the local neighborhood consistence constraints both in color and direction spaces.Moreover, in searching candidate patches, the error tolerance is adaptively decided according to the feature of target patch.Experiment results show that the proposed method can achieve better inpainted results than the state-of-the-art algorithms, especially when dealing with structure and texture images.
李志丹, 和红杰, 尹忠科, 陈帆. 基于Curvelet方向特征的样本块图像修复算法[J]. 电子学报, 2016, 44(1): 150-154.
LI Zhi-dan, HE Hong-jie, YIN Zhong-ke, CHEN Fan. Exemplar Based Image Inpainting Algorithm Using Direction Features of Curvelet Transform. Chinese Journal of Electronics, 2016, 44(1): 150-154.
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2016, Vol. 44 
