中文摘要：

由于在 JPEG2000 图象压缩标准的有损耗的传播，小浪系数的损失重重地影响收到的图象的质量。在这份报纸，我们基于张肌散开(TDWI ) 建议一个新奇小浪 inpainting 模型恢复失踪或损坏的小浪系数。一个混合模型被把结构适应的各向异性的规则化与小浪表示相结合造。它的联系 Euler-Lagrange 方程也为分析它的整齐表演被给。由于在规则化术语的结构张肌的矩阵表示，散开核的形状根据图象特征适应地变化，包括锋利的边，角落和同类的区域。与存在小浪 inpainting 模型相比，建议的那能更适应地并且精确地更好在图象和展览控制几何整齐坚韧性到噪音。另外，一个有效、合适的数字计划被采用改进计算。许多损失情形上的试验性的结果被给表明我们的建议模型的优点。

英文摘要：

Due to the lossy transmission in the JPEG2000 image compression standard,the loss of wavelet coefficients heavily affects the quality of the received image.In this paper,we propose a novel wavelet inpainting model based on tensor diffusion（TDWI）to restore the missing or damaged wavelet coefficients.A hybrid model is built by combining structure-adaptive anisotropic regu-larization with wavelet representation.Its associated Euler-Lagrange equation is also given for analyzing its regularity performance.Owing to the matrix representation of the structure tensor in the regularization term,the shape of diffusion kernel changes adaptivelyaccording to the image features,including sharp edges,corners and homogeneous regions.Compared with existing wavelet inpainting models,the proposed one can control more adaptively and accurately the geometric regularity in the image and exhibits betterrobustness to noise.In addition,an effective and proper numerical scheme is adopted to improve the computation.Experimentalresults on a variety of loss scenarios are given to demonstrate the advantages of our proposed model.