Aimed at the problem of automatic focus and image system quality evaluation in microscopy imaging, a micro-image definition evaluation method is presented by combining multi-scale decomposition tools and absolute gradient operators. The multiscale and multidirectional non-subsampled Shearlet transform is utilized to decompose the input micro image into a low frequency sub-band image and a number of high frequency sub-band images. Combined with the anti-noise threshold setting, the gradient absolute sum values of each sub-band image were calculated. By using the different effects of image sharpness on the low-frequency and high-frequency sub-band coefficients, the ratio of the high-frequency to low-frequency gradient absolute value operator was taken as the final evaluation value of the microscopic image sharpness. The simulation experiment and actual experiments were carried out and the experimental results illustrated that the proposed approach has good monotonicity and anti-noise characteristics. Compared with other classic evaluation algorithms, the presented method obtained superior performance on sensitivity, stability and robustness. It has very good practical application values.
Micro-image definition evaluation using multi-scale decomposition and gradient absolute value
First published at:Jun 01, 2019
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National Natural Science Foundation of China (61805063) and Zhejiang Province Postdoctoral Research
Get Citation: Cui Guangmang, Zhang Keqi, Mao Lei, et al. Micro-image definition evaluation using multi-scale decomposition and gradient absolute value[J]. Opto-Electronic Engineering, 2019, 46(6): 180531.