An improved adaptive correction method for camera distortion

Author(s):  
Shuo Wang ◽  
Shen-min Song ◽  
Xiao-ping Shi
2010 ◽  
Vol 30 (7) ◽  
pp. 2012-2016
Author(s):  
李静 Li Jing ◽  
王军政 Wang Junzheng ◽  
汪首坤 Wang Shoukun ◽  
沈伟 Shen Wei

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1229
Author(s):  
Tomasz Rudnicki

The most critical aspect of assessing a permanent magnet synchronous motor is the problem of correctly measuring the position of the synchronous motor shaft. The purpose of this article was to show the effects of employing an absolute encoder to control a synchronous motor with permanent magnets while encountering disturbances. This problem is often overlooked, but it appears from time to time. The correct measurement of the shaft position eliminates improper motor operation characterized by jerking. The article showed that despite momentary erroneous readings of the shaft’s position, it was still possible to control the permanent magnet synchronous motor (PMSM). This also allows for correct measurement of the motor speed. This paper originally proposed an adaptive correction method for a rotary encoder.


2021 ◽  
Vol 8 ◽  
Author(s):  
Biwei Zhang ◽  
Jiazhu Zhu ◽  
Ke Si ◽  
Wei Gong

Deep learning (DL) has been recently applied to adaptive optics (AO) to correct optical aberrations rapidly in biomedical imaging. Here we propose a DL assisted zonal adaptive correction method to perform corrections of high degrees of freedom while maintaining the fast speed. With a trained DL neural network, the pattern on the correction device which is divided into multiple zone phase elements can be directly inferred from the aberration distorted point-spread function image in this method. The inference can be completed in 12.6 ms with the average mean square error 0.88 when 224 zones are used. The results show a good performance on aberrations of different complexities. Since no extra device is required, this method has potentials in deep tissue imaging and large volume imaging.


2009 ◽  
Vol 48 (33) ◽  
pp. 6426
Author(s):  
Bin Gu ◽  
Dexing Yang ◽  
Dongsheng He ◽  
Shuai Guo ◽  
Zhichun Yang ◽  
...  

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