• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>2014 International Conference on Advances in Engineering and Technology Research >Block based compressive sensing algorithm using Eigen vectors for image compression
【24h】

Block based compressive sensing algorithm using Eigen vectors for image compression

机译：基于特征向量的基于块的压缩感知算法

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The image compression is widely used throughout the multimedia applications and presently many standard techniques are already available, however the in many situation (like after encryption, highly textured etc.) the data compression with the stated techniques are not sufficient, for such cases that relatively new approach called Compressive Sensing can provide a better results as recent research shows. The Compressive Sensing is a concepts primarily used for reduction in reduction in number of observation required for reconstructing the data from linear acquisition system. It fundamentally states that a linear system with N number of equations can be approximated by M equation (M <; N), if system follows sparsely condition. The paper utilizes the same concept for image compression, however the reduction in approximated system equation is performed by calculating the Eigen vectors. The application of Eigen value and vector not only simplifies the process but also provides efficient reconstruction with high compression. The simulation results also verifies the superiority proposed algorithm over previous algorithms by considerable margin.
机译：图像压缩在整个多媒体应用中被广泛使用，并且目前已经有许多标准技术可用，但是在许多情况下（如加密后，高度纹理化等），使用所述技术进行数据压缩还不够，对于这种情况最新研究表明，称为压缩感测的新方法可以提供更好的结果。压缩感测是主要用于减少从线性采集系统重建数据所需的观察次数减少的概念。它从根本上说，如果系统遵循稀疏条件，则具有N个方程组的线性系统可以用M个方程组（M <; N）近似。本文采用相同的概念进行图像压缩，但是通过计算特征向量来执行近似系统方程式的简化。特征值和向量的应用不仅简化了过程，而且还提供了具有高压缩率的有效重构。仿真结果也验证了该算法相对于先前算法的优越性。

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