WMSN图像节点低内存小波变换方法研究  

Image Wavelet Transform on Low Memory Sensor Nodes of WMSN

作　　者：陆明洲[1] 刘志强[1] 沈明霞[1] 刘龙申[1] 杨晓静[2] 周波[3] 

机构地区：[1]南京农业大学江苏省现代设施农业技术与装备工程实验室,南京210031 [2]南京农业大学农业部动物生理生化重点实验室,南京210095 [3]南京农业大学动物科技学院,南京210095

出　　处：《农业机械学报》2014年第4期289-293,188,共6页Transactions of the Chinese Society for Agricultural Machinery

基　　金：农业部公益性行业科研专项资助项目(201003011);江苏省产学研联合创新资金--前瞻性联合研究资助项目(BY2012207);南京农业大学青年科技基金资助项目(KJ2011021)

摘　　要：基于Le Gall 5/3滤波器提出了一种逐行小波变换方法,处理器从图像节点SD卡逐行读出图像信息,完成多级变换后将变换结果行写入SD卡。该方法 SRAM内存需求低,且仅涉及定点整数乘法、加法及移位操作。应用所提方法对一幅256像素×256像素仔猪灰度图像进行小波变换实验,结果表明,该方法以合理的定点运算代价换取了3.968 KB的SRAM开销以及8.718 s的时间开销。为基于小波变换的WMSN节点图像压缩奠定了基础,使农业生产图像在低带宽WMSN上高效传输成为可能。This paper adopts a line based wavelet transform method with the Le Gall 5 /3 filter,in which the image lines are read to SRAM line by line from the SD card and write to the SD card after the multilevel transform operation.The wavelet transform method requires low SRAM memory and involves fixed point integer multiplication,addition,shift operation only.Appling the method to a 256 pixels × 256 pixels gray image of piglets.experimental results show that the SRAM cost of the method is 3.968 KB and the time cost is 8.718 s with a reasonable cost of the arithmetic operation.This study establishes the foundation for the wavelet transform image compression on the image sensor nodes,and makes it possible to transmit the images of agriculture over the low bandwidth WMSN efficiently.

关 键 词：多媒体传感器网络 图像压缩 低内存 逐行小波变换 Le GALL 5 3滤波器 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]