Mesh-Guided Optimized Retexturing for Image and Video pdf
Yanwen Guo, Hanqiu Sun, Qunsheng Peng, Zhongding Jiang
IEEE Trans. on Visualization and Computer Graphics. 2008, 14(2): 426- 439, (IEEE TVCG, SCI, EI)

This paper presents a novel approach for replacing textures of specified regions in the input image and video using stretch-based mesh optimization. The retexturing results have the similar distortion and shading effect conforming to the unknown underlying geometry and lighting conditions. For replacing textures in a single image, two important steps are developed: The stretch-based mesh parameterization incorporating the recovered normal information is deduced to imitate perspective distortion of the region of interest; the Poisson-based refinement process is exploited to account for texture distortion at fine scale. The luminance of the input image is preserved through color transfer in YCbCr color space. Our approach is independent of the replaced textures. Once the input image is processed, any new textures can be applied to efficiently generate the retexturing results. For video retexturing, we propose key-frame-based texture replacement extended and generalized from the image retexturing. Our approach repeatedly propagates the replacement results of key frames to the rest of the frames. We develop the local motion optimization scheme to deal with the inaccuracies and errors of robust optical flow when tracking moving objects. Visibility shifting and texture drifting are effectively alleviated using graphcut segmentation algorithm and the global optimization to smooth trajectories of the tracked points over temporal domain. Our experimental results showed that the proposed approach can generate visually pleasing results for retextured images and video.

A Robust and Fast Non-local Algorithm for Image Denoising pdf
Yanli Liu, Jin Wang, Xi Chen, Yanwen Guo, Qunsheng Peng
Journal of Computer Science and Technology, 2008, 23(2): 270- 279 (JCST, SCI, EI)

In the paper, we propose a robust and fast image denoising method. The approach integrates both Non-Local means algorithm and Laplacian Pyramid. Given an image to be denoised, we first decompose it into Laplacian pyramid. Exploiting the redundancy property of Laplacian pyramid, we then perform non-local means on every level image of Laplacian pyramid. Essentially, we use the similarity of image features in Laplacian pyramid to act as weight to denoise image. Since the features extracted in Laplacian pyramid are localized in spatial position and scale, they are much more able to describe image, and computing the similarity between them is more reasonable and more robust. Also, based on the efficient Summed Square Image (SSI) scheme and Fast Fourier Transform (FFT), we present an accelerating algorithm to break the bottleneck of non-local means algorithm �?similarity computation of compare windows. After speedup, our algorithm is fifty times faster than original non-local means algorithm. Experiments demonstrated the effectiveness of our algorithm.

Tone Adjustment of Underexposed Images Using Dynamic Range Remapping pdf
Yanwen Guo, Xiaodong Xu
Pacific-Rim Conference on Multimedia 2008, Springer LNCS. 5353: 515-524.

We present a new method for automatically adjusting the tonal values of underexposed digital images. We make the most of the dynamic range of digital images, and adjust the tonal values through dynamic range remapping, with a specifically defined tone mapping operator. The operator comprises two concatenate terms. The first one is a global operator that adjusts the tonal values of underexposed image with a linear scale transformation as well as a nonuniform intensity reduction function. The second one is a local operator used for noise suppression and detail enhancement. With such operator, tone values of underexposed images are faithfully adjusted. Meanwhile, noises are suppressed without introducing noticeable artifacts into resulting images. Our method runs with high efficiency. Experimental results demonstrate its effectiveness.

一种基于网格参数化的图像适应方法 pdf
时健 郭延�? 杜振�?张福�?彭群�?strong>
软件学报, 中国计算机图形学大会2008 (通信作�?

图像适应是指将高分辨率的数字图像显示在手机、PDA等屏幕较小的显示终端上的过程.提出一种全新的基于网格参数化的图像适应方法,该方法的关键在于把图像表示为特征网格,从而将图像适应问题转化为网格的参数�?即求取一个与该特征网格同拓扑,且具有目标屏幕尺寸的网格.为了突出图像中的重要物体,该方法建立了源图像对应的特征网格与图像显著度的关�?通过优化基于显著度伸长的网格参数化的能量来求解适应图像的网�?然后借助纹理映射生成适应图像.另外,该方法在参数化的过程中增加了对显著区域和背景结构的约�?能够在保持并增强图像中重要物体的同时,使适应图像的结构不发生明显形变.该方法能够方便地处理具有复杂背景和包含多目标物体的图像的适应问题.实验结果显示了该方法的有效�?

图像和视频亮度的自动调整 pdf
王想 郭延�? 杜振�?武港�? 张福�?彭群�?strong>
电子学报, (Acta Electronica Sinica 通信作�? 中国计算机图形学大会2008

对曝光不足的图像和视频进行亮度调整具有重要的理论研究意义和实际应用价�?本文提出一种基于梯度域操作的图像和视频亮度自动调整算法.对于静态图�?算法首先将图像分割为不同的亮度区�?然后分别计算各区域的亮度调整算子;最后通过求解一个梯度约束方程得到结果图�?我们进而将该算法延伸到视频,首先选取若干关键帧并使用上述图像亮度调整算法进行处理;然后对非关键帧进行分割并通过光流算法确定非关键帧上的分割区域与前后关键帧区域的对应关�?最后利用对应关系通过关键帧区域的亮度调整算子以及调整后的亮度指导非关键帧上各区域的亮度调�?并生成结果视频序�?本文算法可以有效处理空间和时间上曝光不足和不均的图像和视�?并能够较好地保持图像、视频的细节纹理信息,实验结果表明了算法的有效�?