提出了一种在梯度域中进行无缝图像处理的方法.在一般的整体变分模型中引入待处理区域的梯度场,得到一个扩展的整体变分模型,称为梯度场整体变分(gradient field totalvariation,GFTV)模型.无缝处理通过最小化模型函数来实现.基于GFTV...提出了一种在梯度域中进行无缝图像处理的方法.在一般的整体变分模型中引入待处理区域的梯度场,得到一个扩展的整体变分模型,称为梯度场整体变分(gradient field totalvariation,GFTV)模型.无缝处理通过最小化模型函数来实现.基于GFTV模型的方法可应用于以下无缝图像处理:在图像中无缝地插入新的目标;无缝地修改图像中某个区域的纹理、光照等外观;图像的无缝拼接等.展开更多
This paper reports some researches on distribution of large volume image data using techniques of the Mixed Mode of Java Servlet and COM on Web. The architecture and key technologies are discussed in detail. The web d...This paper reports some researches on distribution of large volume image data using techniques of the Mixed Mode of Java Servlet and COM on Web. The architecture and key technologies are discussed in detail. The web distribution system of image is implemented and the system is tested by the application instances. At last, the advantages and disadvantages for this web image distribution mode are analyzed.展开更多
文摘提出了一种在梯度域中进行无缝图像处理的方法.在一般的整体变分模型中引入待处理区域的梯度场,得到一个扩展的整体变分模型,称为梯度场整体变分(gradient field totalvariation,GFTV)模型.无缝处理通过最小化模型函数来实现.基于GFTV模型的方法可应用于以下无缝图像处理:在图像中无缝地插入新的目标;无缝地修改图像中某个区域的纹理、光照等外观;图像的无缝拼接等.
文摘This paper reports some researches on distribution of large volume image data using techniques of the Mixed Mode of Java Servlet and COM on Web. The architecture and key technologies are discussed in detail. The web distribution system of image is implemented and the system is tested by the application instances. At last, the advantages and disadvantages for this web image distribution mode are analyzed.