首页> 外文会议>International Conference on Wireless Communications, Signal Processing and Networking >An Improved and Optimized Content-Aware Resizing Algorithm for Images with Densely Situated Foreground Objects
【24h】

An Improved and Optimized Content-Aware Resizing Algorithm for Images with Densely Situated Foreground Objects

机译:改进和优化的具有密集位置的前景对象的图像的内容感知调整大小算法

获取原文

摘要

An image in general consists of a combination of significant objects in the foreground and not-so-significant objects in the background. Content aware image resizing or seam carving is a process of resizing an image while maintaining the significant objects (the foreground) in proper visual saliency. The standard algorithms, however, often generate unpredictable distortions in images with densely situated foreground objects. The optimized content aware image resizing (OCAIR) algorithm presented herein, uses iterative graph cuts and edge detection to generate an energy map based on the important sections of the image, so that the resized image does not exhibit unpredictable artefacts. An improved energy map generation algorithm is designed here, which not only marks out the important foreground elements quicker than previously available techniques, but also uses that information to quantity the amount of distortion (if any) that might take place after adding or deleting seams by means of calculating a distortion factor. The process being considerably faster than previous algorithms, allows precise modifications to the input parameters to obtain a well-doctored final image.
机译:通常,图像由前景中的重要对象和背景中的不太重要的对象组成。内容感知的图像大小调整或接缝雕刻是在保持重要的对象(前景)处于适当的视觉显着性的同时调整图像大小的过程。然而,标准算法经常在前景对象密集放置的图像中产生不可预测的失真。本文介绍的优化的内容感知图像大小调整(OCAIR)算法使用迭代图割和边缘检测来基于图像的重要部分生成能量图,因此调整大小后的图像不会显示出不可预测的伪影。这里设计了一种改进的能量图生成算法,该算法不仅比以前的可用技术更快地标识出重要的前景元素,而且还使用该信息来量化添加或删除接缝后可能发生的变形量(如果有)。计算失真因子的方法。该过程比以前的算法快得多,可以对输入参数进行精确的修改,以获取经过精心设计的最终图像。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号