摘要
提出了基于最小各向同性小波滤波的图像清晰度识别方法,对二维最小各向同性小波滤波提取图像特征进行了研究.直接将原始图像通过带通小波滤波器G0获得图像边缘信息,结合图像能量分析,建立了基于小波滤波的图像清晰度评价函数.利用构建的显微镜自动对焦实验平台,比较分析了基于小波滤波和拉普拉斯的评价方法.实验结果表明,采用基于各向同性小波滤波的自动对焦算法有更好的综合自动对焦性能.
An identification method of image definition based on a minimum isotropy wavelet was proposed and the image edge detection based two dimensional minimum isotropy wavelet transform was studied. The original image goes through the band-pass wavelet filter Go directly to obtain the image edge information. Combining with image energy analysis, an improved focusing evaluation function can be obtained. The evaluation function based on the wavelet filtration was compared with the evaluation function based on the Laplaeian operator by using the auto-focusing system of a microscope. The experiment results indicate that the auto-focusing algorithm based on the isotropy wavelet filtration has good performance
出处
《光子学报》
EI
CAS
CSCD
北大核心
2008年第2期395-399,共5页
Acta Photonica Sinica
基金
国家自然科学基金(60672063)
浙江省科技计划项目(021105778)资助
关键词
图像处理
图像清晰度
小波滤波
对焦评价函数
显微镜
Image processing
Image definition
Wavelet filtration
Focusing evaluation function
Microscope
