Image Retargeting Using Mesh Parametrization pdf
Yanwen Guo, Feng Liu, Jian Shi, Zhihua Zhou, Michael Gleicher
IEEE Trans. on Multimedia 2009, 11(4):856-867 (IEEE TMM, SCI, EI).


Image retargeting aims to adapt images to displays of small sizes and different aspect ratios. Effective retargeting requires emphasizing the important content while retaining surrounding context with minimal visual distortion. In this paper, we present such an effective image retargeting method using saliency-based mesh parametrization. Our method first constructs a mesh image representation that is consistent with the underlying image structures. Such a mesh representation enables easy preservation of image structures during retargeting since it captures underlying image structures. Based on this mesh representation, we formulate the problem of retargeting an image to a desired size as a constrained image mesh parametrization problem that aims at finding a homomorphous target mesh with desired size. Specifically, to emphasize salient objects and minimize visual distortion, we associate image saliency into the image mesh and regard image structure as constraints for mesh parametrization. Through a stretch-based mesh parametrization process we obtain the homomorphous target mesh, which is then used to render the target image by texture mapping. The effectiveness of our algorithm is demonstrated by experiments.

Pores-Preserving Face Cleaning Based on Improved Empirical Mode Decomposition pdf
Yanli Liu, Xiaogang Xu, Yanwen Guo, Jin Wang, Xin Duan, Xi Chen and Qunsheng Peng
Journal of Computer Science and Technology 2009. 24(3) 557-567 (SCI, EI)


In this paper,we propose a novel method of cleaning up facial imperfections such as bumps and blemishes that may detract from a pleasing digital portrait.Contrasting with traditional methods which tend to blur facial details, our method fully retains fine scale skin textures(pores etc.) of the subject.Our key idea is to find a quantity,namely normalized local energy,to capture different characteristics of fine scale details and distractions,based on empirical mode decomposition,and then build a quantitative measurement of facial skin appearance which characterizes both imperfections and facial details in a unified framework.Finally,we use the quantitative measurement as a guide to enhance facial skin.We also introduce a few high-level,intuitive parameters for controlling the amount of enhancement.In addition,an adaptive local mean and neighborhood limited empirical mode decomposition algorithm is also developed to improve in two respects the performance of empirical mode decomposition.It can effectively avoid the gray spots effect commonly associated with traditional empirical mode decomposition when dealing with high-nonstationary images.

Binary Alpha-Plane Assisted Fast Motion Estimation of Video Objects in Wavelet Domain pdf
Chuan-Ming Song, Xiang-Hai Wang, Yanwen Guo, and Fu-Yan Zhang
IEEE Data Compression Conference 2009. Salt Lake City, Utah, USA. (IEEE DCC, Poster)


Summary form only given. Shift-variance and computational complexity are bottleneck of existing wavelet-based motion estimation (ME). Moreover, to the best of our knowledge, few works have been reported on wavelet-domain ME of video objects (VOs). In this paper, we present an efficient wavelet-domain approach to ME of arbitrarily shaped VOs.

噪声方差未知的小波域中非局部均值图像去�?nbsp;pdf
刘艳�? 郭延�?, 王进, 彭群�?/span>
计算机辅助设计与图形学学�?2009, 21(4)


为了有效地去除噪�?获得细节清晰的图�?提出一种噪声参数未知情况下基于小波分析的图像去噪算�?首先对图像上交互选定的不含细节的样本区域进行小波分解,根据噪声方差在不同尺度、不同方向子带内的映像建立噪声的特征向量;利用此特征向量计算小波分解后高频子带内各小波系数之间的相似度,把该相似度作为权值对当前小波系数进行调整.实验结果表明,文中算法对于噪声方差未知的图像不仅能有效地去除噪�?而且能保持图像的边缘信息,获得较好的去噪效�?对实拍的含噪数码照片进行测试的效果理�?