ROI-based Watermarking Scheme for JPEG 2000

A new region of interest (ROI)-based watermarking method for JPEG 2000 is presented. The watermark is embedded into the host image based on the characteristics of the ROI to protect rights to the images. This scheme integrates the watermarking process with JPEG 2000 compression procedures. Experimental results have demonstrated that the proposed watermark technique successfully survives JPEG 2000 compression, progressive transmission, and principal attacks.     

基于小波多分辨率分析的指横纹定位新算法

针对指横纹感兴趣区域(ROI)难以准确定位的问题,在明确提出指横纹ROI定义的前提下,提出利用小波多分辨率分析进行指横纹ROI自动检测定位的新算法.该方法利用纹理相似性原理,在高频子图采用基于特征向量和区域生长法产生指横纹的候选子区域集合,然后利用低频子图Radon投影得到的指横纹的区域特征对候选子区域进行验证,最后结合直线拟合手指轮廓得到指横纹在原图的有效位置,最终实现指横纹ROI的精准定位.实验证明该算法不仅能有效克服噪声以及手形姿态变化的影响,并且对多种情况有很强的鲁棒性.     

基于感兴趣区梯度方向直方图的行人检测

针对以梯度方向直方图作为人体特征的行人检测存在向量维数较大、检测时间较长的问题,提出基于感兴趣区梯度方向直方图的行人检测方法,分别在头部及四肢等重点区域计算梯度方向直方图,有效地减少了向量维数。实验结果表明,该方法在检测率基本不变的情况下提高了检测速度。     

A New Medical Image Enhancement Based on Human Visual Characteristics

Study of image enhancement shows that the quality of image heavily relies on human visual system. In this paper, we apply this fact effectively to design a new image enhancement method for medical images that improves the detail regions. First, the eye region of interest （ROI） is segmented; then the Un-sharp Masking （USM） is used to enhance the detail regions. Experiments show that the proposed method can effectively improve the accuracy of medical image enhancement and has a significant effect.     

DOLAR: virtualizing heterogeneous information spaces to support their expansion

Users expect applications to successfully cope with the expansion of information as necessitated by the continuous inclusion of novel types of content. Given that such content may originate from ‘not‐seen thus far’ data collections and/or data sources, the challenging issue is to achieve the return of investment on existing services, adapting to new information without changing existing business‐logic implementation. To address this need, we introduce DOLAR (Data Object Language And Runtime), a service‐neutral framework which virtualizes the information space to avoid invasive, time‐consuming, and expensive source‐code extensions that frequently break applications. Specifically, DOLAR automates the introduction of new business‐logic objects in terms of the proposed virtual ‘content objects’. Such user‐specified virtual objects align to storage artifacts and help realize uniform ‘store‐to‐user’ data flows atop heterogeneous sources, while offering the reverse ‘user‐to‐store’ flows with identical effectiveness and ease of use. In addition, the suggested virtual object composition schemes help decouple business logic from any content origin, storage and/or structural details, allowing applications to support novel types of items without modifying their service provisions. We expect that content‐rich applications will benefit from our approach and demonstrate how DOLAR has assisted in the cost‐effective development and gradual expansion of a production‐quality digital library. Experimentation shows that our approach imposes minimal overheads and DOLAR‐based applications scale as well as any underlying datastore(s). Copyright © 2011 John Wiley & Sons, Ltd.     

A general fan-beam reconstruction algorithm for free-form trajectories

In this paper we develop a general exact fan-beam reconstruction algorithm for free-form trajectories not only closed but also unclosed, based on the fan-beam reconstruction formula recently developed by Noo et al.. A mathematical proof is then provided with the geometrical explanation of equi-spatial detectors. With this algorithm we can obtain exact region of interest (ROI) reconstruction if and only if every projecting line passing through the ROI intersects the free-form source trajectory, when the projections are not truncated. Furthermore, under the condition that the source-to-detectors distance changes slowly enough relative to the length itself, we obtain a very good approximate reconstruction algorithm, which is the same as the algorithm of the circular trajectory except that the source-to-detectors distance is a function of the rotation angle. Then the algorithms are tested using the Shepp-Logan phantom and the experiment shows that the algorithms can get perfect numerical results.     

卫星云图感兴趣区域自动提取方法研究

卫星云图中人们感兴趣的区域(ROI)往往是各类云团,针对卫星云图内容的复杂性,利用直方图模糊加权C均值聚类方法实现云图的图像分割,对分割结果进行后处理,最终获取云图内的感兴趣区域。常规聚类方法需要人工指定类个数,影响了ROI提取过程的自动化程度。引入修正聚类评价指标,基于该指标实现最佳类别个数的自动确定。云图分割是感兴趣区域提取过程的关键,采用的直方图模糊加权C均值聚类方法在原有算法基础上,引入样本权重概念,使得聚类过程更为合理;同时将聚类对象由原始像素转换为灰度直方图,提高了聚类过程执行效率。实验结果表明设计的感兴趣区域提取方法能较为准确地分辨出陆地、水体、低云、中云、卷云、对流云六类区域,提取结果与客观实际一致。     

一种基于EZW的ROI图像联合压缩加密算法

提出一种基于EZW编码的ROI图像联合压缩加密算法,阐述了上下文修正和判决修正的原理及实现,对所提出算法的安全性进行了评估。对算法进行仿真,结果表明相对于原始图像压缩算法,该算法的重构图像基本具有相同的压缩效率;相较于提升系数的ROI方法,该算法采用小波域图像分割,不需要对ROI形状信息进行编码,并可灵活调整ROI与背景区域(BG)的重构质量;相较于区间分裂算术编码器而言,该算法采用自适应算术编码,可获得更好的安全性;结合比特平面编码技术,使用不同密钥对ROI不同小波分辨力的系数分别加密,实现分辨力选择性加密,以满足不同应用需求。     

基于JPEG2000的遥感图像感兴趣区域编码新算法及其VLSI设计

为解决空间遥感图像数据量及信道带宽之间的矛盾,该文提出一种基于JPEG2000的感兴趣区域(Region Of Interest, ROI)编码算法。主流的JPEG2000 ROI编码算法难以兼顾ROI质量和系统计算量,且在低码率编码时有完全丢失背景的隐患。该算法通过精确控制各子带中背景系数的精度,使ROI分配到更多码流。并引入了人眼视觉特性,使较少的背景码流产生尽量好的视觉效果。另外,根据该算法提出了针对矩形ROI的超大规模集成电路(VLSI)设计,此设计经过简单调整,亦可适用于主流的ROI编码算法。测试结果表明,该算法在ROI质量和重建图像视觉效果上均表现优异,且支持任意形状ROI编码,兼容JPEG2000协议。该VLSI设计仅使JPEG2000系统运行时间增加一个周期,具有极高的吞吐率,可满足实时处理要求。     

实现图像感兴趣区域渐进编码的新方法——一种改进的嵌入式零树小波编码算法

在分析了Shapiro的嵌入式零树小波编码算法的基础上，针对其效率的不足提出了一种改进方法。本算法通过识别重要子带，而不是EZW中的重要系数，大大减少了需要编码的零树的数量，因而节省了时间。在此改进的基础上，结合坐标数据压缩算法实现了对图像感兴趣区域的渐进编码。该算法可在接收到图像的全部编码数据之前，首先实现感光趣区域的高品质重建，且编码效率也有明显提高。