面向视觉传感器网络的一种低错误敏感度图像压缩算法
首发时间:2012-01-20
摘要:传统的JPEG图像压缩算法由于对数据进行了高度压缩,致使1bit所含信息量过高,部分数据的丢失将导致大面积图像受损,不适合于视觉传感器网络。本文利用交织嵌入的思想,在不改变压缩数据数据量大小的情况下,将交织错位后的原始图像的二值信息作为副本嵌入到小波压缩数据中,以副本图像来对因丢包而造成的破损区进行修复,由此提出了一种抗丢包的低错误敏感度的图像压缩算法(LESIC:Low Error -Sensitivity Image Compression )。理论分析和实验结果表明,相比JPEG算法,LESIC算法在网络传输质量下降时,可降低图像对数据丢包的敏感性,有着更好的图像传输质量。
For information in English, please click here
A Low Error-Sensitivity Image Compression Algorithm for Visual Sensor Networks
Abstract:The high data compression ratio by traditional JPEG algorithm means 1bit compressed data contain too much information, which result in that even a little data loss will lead to a heavy damage to the image. Thus the traditional JPEG image compression algorithm may not be suitable for visual sensor networks.On considering this reason, we propose a anti-loss Low Error-Sensitivity Image Compression Algorithm(LESIC) use the idea of interleaved embed. As a copy of the original image,the interleaved binary image will be embedded into the data of wavelet compression without changing the size of the compression data. Therefore,we can use the copy image to repair the damaged area due to the data loss.Both theoretical analysis and experimental results show that the propopsed image compression algorithm LESIC obviously reduce the sensitivity of the image quality to data loss and hold a more effective image transmission than that of JPEG.
Keywords: Visual Sensor Networks Interleaved Embed Low Error-Sensitivity Image Compression
论文图表:
引用
No.****
同行评议
共计0人参与
勘误表
面向视觉传感器网络的一种低错误敏感度图像压缩算法
评论
全部评论0/1000