摘要
通过分析昆虫自由飞行状态下结构光光条图像的特点,提出了一种用于提取昆虫运动变形测量中弱光条中心点的图像处理方法。该方法根据图像的灰度分布情况对图像进行分块,采用小波理论对图像消噪,利用模糊增强和小波同态滤波相结合的算法增强各图像的弱光条信号,再应用steger算法提取弱光条中心点的亚像素位置。给出几种算法实验结果的比较和分析,表明该方法成功实现了弱光条信号中心点的提取,并有效抑制了噪声和干扰。
An image processing method for extracting central points of weak stripes for the measurement of kinetic deformation of free-fly insect wings was proposed by analyzing the characteristic of structured-light-stripe image. With the method, sub-pixel position of weak strips central points were extracted with steger algorithm by dividing the image according to gray value distributing at first, then eliminating noise using wavelet theory, finally enhancing weak strips of each image using fuzzy enhancement and wavelet homomorphic filtering methods. Experimental result was compared with other methods and analyzed. The proposed approach extracts weak strips central points successfully, and restrains noise and interference efficiently.
出处
《光学技术》
EI
CAS
CSCD
北大核心
2007年第3期341-344,共4页
Optical Technique
基金
国家杰出青年科学基金资助项目(50125518)
关键词
图像处理
结构光
模糊增强
小波同态滤波
光条提取
image processing
structured-light
fuzzy enhancement
wavelet homomorphic filtering
stripes extraction
