ID 原文 译文
21325 基于局部算子的全变差(TV)模型在对纹理图像着色时，会出现颜色扩散不均匀，着色范围区域较小等问题。 The traditional Total Variation (TV) model based on local operators for texture image colorizationhas some problems, such as inhomogeneous color diffusion, small coloring ranges and so on.
21326 为了解决上述问题，该文提出基于非局部算子的耦合全变差图像着色模型，结合交替方向乘子法(ADMM)，设计出相应的数值求解算法，并给出该算法的收敛性结果。 In order to solve these problems, a coupled total variation model based on nonlocal operators is presented for image colorization,and the correspond numerical algorithm is designed to solve the model by incorporating the Alternating Direction Method of Multipliers (ADMM), and the convergence result of the algorithm is given.
21327 该模型充分利用像素邻域亮度之间的相似性进行颜色扩散，能有效避免仅利用亮度边缘信息进行局部扩散导致颜色扩散不均匀的问题。 The proposed model makes full use of the similarity between the brightness of the pixel areas to perform color diffusion, which can effectively avoid the problem of inhomogeneous color diffusion due to local diffusion only using the brightness edge information.
21328 数值实验结果表明，该模型在快速着色的同时，能有效解决颜色在纹理等细节处扩散不均匀的问题。 The experimental results are given to show that the model can effectively solve the problem of in homogeneous color diffusion at textures and other details while fast colorizing.
21329 在采用压缩感知的阵列失效单元诊断方法中，结构化随机采样策略的运用对测量矩阵性能造成不利影响。 The structured random sampling strategy adopted in array diagnosis has negative influence on the performance of measurement matrix.
21330 针对这一问题，该文提出一种基于确定性压缩感知采样策略的阵列失效单元远场诊断方法。 Therefore, a compressed sensing based deterministic sampling strategy todiagnose defective array elements using far-field measurements is investigated in this paper.
21331 首先在失效单元个数满足稀疏性的前提下构造差异性阵列并将其激励作为稀疏向量， In the case of thenumber of failed elements satisfies sparsity, the sparse vector is constructed by subtracting incentives ofreference array without failures and the array under test.
21332 其次利用所提方法构造确定性部分傅里叶矩阵(DPFM)作为测量矩阵， Deterministic Partial Fourier Matrix (DPFM) is thenformulated by the proposed strategy as the measurement matrix.
21333 最后采用l1范数最小化算法对稀疏向量进行重构，从而实现对失效单元的高概率精确诊断。 Finally, accurate diagnosis with highprobability is achieved by l1 norm minimization.
21334 理论分析和仿真实验表明，所提方法有效消除了采样位置的随机分布特性对测量矩阵性能造成的不利影响，简化了采样过程，提高了诊断成功概率。 Theoretical analysis and simulation results demonstrate that the proposed method can avoid the adverse impact on the performance of measurement matrix effectively arising from the random distribution of sampling positions, simplify the sampling procedure and improve the probability of success rate of diagnosis.