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A Novel Image Completion Algorithm Based on Planar Features
( Mang Xiao ),( Yunxiang Liu ),( Li Xie ),( Qiaochuan Chen ),( Guangyao Li ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.8
A novel image completion method is proposed that uses the advantage of planar structural information to fill corrupted portions of an image. First, in estimating parameters of the projection plane, the image is divided into several planes, and their planar structural information is analyzed. Second, in calculating the a priori probability of patch and patch offset regularity, this information is converted into a constraint condition to guide the process of filling the hole. Experimental results show that the proposed algorithm is fast and effective, and ensures the structure continuity of the damaged region and smoothness of the texture.
Image Completion using Belief Propagation Based on Planar Priorities
( Mang Xiao ),( Guangyao Li ),( Yinyu Jiang ),( Li Xie ),( Ye He ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.9
Automatic image completion techniques have difficulty processing images in which the target region has multiple planes or is non-facade. Here, we propose a new image completion method that uses belief propagation based on planar priorities. We first calculate planar information, which includes planar projection parameters, plane segments, and repetitive regularity extractions within the plane. Next, we convert this planar information into planar guide knowledge using the prior probabilities of patch transforms and offsets. Using the energy of the discrete Markov Random Field (MRF), we then define an objective function for image completion that uses the planar guide knowledge. Finally, in order to effectively optimize the MRF, we propose a new optimization scheme, termed Planar Priority-belief propagation that includes message-scheduling-based planar priority and dynamic label cropping. The results of experiment show that our approach exhibits advanced performance compared with existing approaches.
Image Completion Using Similarity Analysis and Transformation
Mang Xiao,Guangyao Li,Yunlan Tan,Jie Qin 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.4
Image completion is aim to fill the missing regions in images. A robust completion technique using similarity analysis and transformation is proposed to address this problem. Firstly, in order to decrease the search space of patches, random mapping method is used to analyze texture regions which have similar structure and texture with damaged regions. Secondly, geometric and photometric transformations of image are adopted to find the best patches. Thirdly, increasing the accuracy of the structure propagation, a priority calculation method is optimized based on confidence factor and edge information. Finally, a number of examples on real and synthetic images show the effectiveness of our algorithm for image completion.
Qing-Yuan Xu,Xiao-Dong Li,Mang-Mang Lv 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.2
Almost all of the existing research achievements in Iterative Learning Control (ILC) hitherto have beenfocused on One-Dimensional (1-D) dynamical systems. Few ILC researches are related to Two-Dimensional FornasiniMarchesina Model (2-D FMM). In this paper, an adaptive ILC approach is proposed for 2-D FMM systemwith non-repetitive reference trajectory under random boundary condition. The proposed adaptive ILC algorithmlearns the coefficient matrices of the system and updates the control input iteratively. As the times of iteration goesto infinity, the ILC tracking error outside the boundary tends to zero and all system signals keep bounded in thewhole ILC process. Illustrative examples are provided to verify the validity of the proposed adaptive ILC algorithm.