浏览全部资源
扫码关注微信
1.淮阴师范学院 计算机科学与技术学院,江苏 淮安 223300
2.淮阴师范学院 物理与电子电气工程学院,江苏 淮安 223300
[ "郭立强(1982-),男,吉林汪清人,副教授,2005年和2008年于延边大学分别获得学士和硕士学位,2011年于中科院长春光机所获得博士学位,主要从事图像处理、计算机视觉与模式识别方面的研究。E-mail: guolq@hytc.edu.cn" ]
收稿日期:2020-10-26,
修回日期:2020-12-20,
纸质出版日期:2021-07-15
移动端阅览
郭立强,刘恋.结合斜变换与方差的图像聚焦测度[J].光学精密工程,2021,29(07):1731-1739.
GUO Li-qiang,LIU Lian.Image focus measure based on slant transform and variance[J].Optics and Precision Engineering,2021,29(07):1731-1739.
郭立强,刘恋.结合斜变换与方差的图像聚焦测度[J].光学精密工程,2021,29(07):1731-1739. DOI: 10.37188/OPE.2020.0555.
GUO Li-qiang,LIU Lian.Image focus measure based on slant transform and variance[J].Optics and Precision Engineering,2021,29(07):1731-1739. DOI: 10.37188/OPE.2020.0555.
针对相机和电子显微镜等成像设备在自动对焦过程中聚焦测度易受噪声干扰的问题,将图像处理中的斜变换与统计学中的方差相结合,提出一种具有噪声鲁棒性的聚焦测度。将图像进行分块处理,便于后续获取每个局部子图像的清晰度指标。计算每一个子图像的斜变换来得到频域系数。在变换域中,计算中频系数的绝对值并对它进行累加求和作为各子图像的清晰度指标。最后,计算各子图像清晰度的方差,将该方差作为整幅图像的聚焦测度值。通过提取局部子图像的中频信息并结合全局的方差求解的方法可以使聚焦测度具有较高的噪声鲁棒性;通过在LIVE图像数据库的实验结果表明:本文方法的噪声鲁棒性优于现有经典算法,其SDA和离散度客观评价指标相比于鲁棒性较好的索贝尔梯度熵算法平均提高了20.27%和125.61%。
Focus measure is easy to be interfered by the noise in the autofocusing process for a camera and electronic microscope. In order to solve this problem, we combine the slant transform in image processing with the variance in statistics to propose a novel focusing measure with noise robustness. First, the image is divided into small blocks to facilitate the subsequent acquisition of the sharpness index of each local sub image. Then, we perform the slant transform on each sub image to obtain the frequency coefficients. In the transform domain, we calculate the absolute value of the mid-frequency coefficient, and perform the summation operation to obtain the sharpness index of each sub image. Finally, the variance of each sub image sharpness index is calculated, and the result is taken as the final focus measure of the whole image. By extracting the mid-frequency information of local sub images and solving the global variance, the proposed focus measure has strong noise robustness. The experiments on LIVE image database indicate that compared with the typical focus measure, the noise robustness of the proposed method is better than the existing classical algorithms, where the sharpness detection ability (SDA) and the discreteness evaluation indexes are improved by 20.27% and 125.61% averagely.
KRISTAN M , PERŠ J , PERŠE M , et al . A Bayes-spectral-entropy-based measure of camera focus using a discrete cosine transform [J]. Pattern Recognition Letters , 2006 , 27 ( 13 ): 1431 - 1439 .
张从鹏 , 曹文政 , 徐明刚 , 等 . 结核杆菌涂片显微视觉检测系统的自动聚焦 [J]. 光学 精密工程 , 2018 , 26 ( 6 ): 1480 - 1488 .
ZHANG C P , CAO W ZH , XU M G , et al . Automatic focusing of micro-vision detection system of Mycobacterium tuberculosis smear [J]. Optics and Precision Engineering , 2018 , 26 ( 6 ): 1480 - 1488 . (in Chinese)
姜志国 , 韩冬兵 , 袁天云 , 等 . 基于全自动控制显微镜的自动聚焦算法研究 [J]. 中国图象图形学报 , 2004 , 9 ( 4 ): 396 - 401 .
JIANG ZH G , HAN D B , YUAN T Y , et al . Study on auto focusing algorithm for automatic microscope [J]. Journal of Image and Graphics , 2004 , 9 ( 4 ): 396 - 401 . (in Chinese)
朱文艳 , 周连群 , 张芷齐 , 等 . 微孔式数字PCR荧光芯片的自动对焦 [J]. 光学 精密工程 , 2020 , 28 ( 9 ): 2065 - 2075 .
ZHU W Y , ZHOU L Q , ZHANG ZH Q , et al . Autofocus of microarray digital PCR fluorescent chip [J]. Optics and Precision Engineering , 2020 , 28 ( 9 ): 2065 - 2075 . (in Chinese)
XIA X H , YAO Y S , LIANG J , et al . Evaluation of focus measures for the autofocus of line scan cameras [J]. Optik , 2016 , 127 ( 19 ): 7762 - 7775 .
何宝凤 , 丁思源 , 魏翠娥 , 等 . 三维表面粗糙度测量方法综述 [J]. 光学 精密工程 , 2019 , 27 ( 1 ): 78 - 93 .
HE B F , DING S Y , WEI C E , et al . Review of measurement methods for areal surface roughness [J]. Optics and Precision Engineering , 2019 , 27 ( 1 ): 78 - 93 . (in Chinese)
GROEN F C A , YOUNG I T , LIGTHART G . A comparison of different focus functions for use in autofocus algorithms [J]. Cytometry , 1985 , 6 ( 2 ): 81 - 91 .
GEUSEBROEK J M , CORNELISSEN F , SMEULDERS A W M , et al . Robust autofocusing in microscopy [J]. Cytometry , 2000 , 39 ( 1 ): 1 - 9 .
NAYAR S K , NAKAGAWA Y . Shape from focus [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence , 1994 , 16 ( 8 ): 824 - 831 .
RUDIN L I , OSHER S , FATEMI E . Nonlinear total variation based noise removal algorithms [J]. Physica D: Nonlinear Phenomena , 1992 , 60 ( 1 / 2 / 3 / 4 ): 259 - 268 .
ZEDER M , PERNTHALER J . Multispot live-image autofocusing for high-throughput microscopy of fluorescently stained bacteria [J]. Cytometry Part A , 2009 , 75 A( 9 ): 781 - 788 .
WEE C Y , PARAMESRAN R . Measure of image sharpness using eigenvalues [J]. Information Sciences , 2007 , 177 ( 12 ): 2533 - 2552 .
LIU S X , LIU M H , YANG Z Y . An image auto-focusing algorithm for industrial image measurement [J]. EURASIP Journal on Advances in Signal Processing , 2016 , 2016, 70 ( 1 ): 1 - 16 .
XIA X H , YIN L J , YAO Y S , et al . Combining two focus measures to improve performance [J]. Measurement Science and Technology , 2017 , 28 ( 10 ): 105401 .
LI Y , TANG T L , HUANG W . A robust auto-focus measure based on inner energy [J]. Optoelectronics Letters , 2017 , 13 ( 4 ): 309 - 313 .
AHMAD B , MUTAHIRA H , LI M , et al . Measuring focus quality in color space [C]. 2019 2nd International Conference on Communication , Computing and Digital systems (C-CODE) . March 6-7, 2019 , Islamabad , Pakistan. IEEE, 2019 : 115 - 119 .
VU P V , CHANDLER D M . A fast wavelet-based algorithm for global and local image sharpness estimation [J]. IEEE Signal Processing Letters , 2012 , 19 ( 7 ): 423 - 426 .
LIU Y P , JIN J , WANG Q , et al . Phases measure of image sharpness based on quaternion wavelet [J]. Pattern Recognition Letters , 2013 , 34 ( 9 ): 1063 - 1070 .
LEE S Y , KUMAR Y , CHO J M , et al . Enhanced autofocus algorithm using robust focus measure and fuzzy reasoning [J]. IEEE Transactions on Circuits and Systems for Video Technology , 2008 , 18 ( 9 ): 1237 - 1246 .
ZHANG Z , LIU Y , XIONG Z H , et al . Focus and blurriness measure using reorganized DCT coefficients for an autofocus application [J]. IEEE Transactions on Circuits and Systems for Video Technology , 2018 , 28 ( 1 ): 15 - 30 .
MAHMOOD M T , CHOI T S . Focus measure based on the energy of high-frequency components in the S transform [J]. Optics Letters , 2010 , 35 ( 8 ): 1272 - 1274 .
ENOMOTO H , SHIBATA K . Orthogonal transform coding system for television signals [J]. IEEE Transactions on Electromagnetic Compatibility , 1971 , EMC- 13 ( 3 ): 11 - 17 .
SHEIKH H R . LIVE Image Quality Assessment Database [OL]. http://live.ece.utexas.edu/research/quality http://live.ece.utexas.edu/research/quality .
0
浏览量
785
下载量
2
CSCD
关联资源
相关文章
相关作者
相关机构