Title :
An improved focusing algorithm based on image definition evaluation
Author :
Hui, Li ; Chengyu, Fu
Author_Institution :
Inst. Of Opt. & Electron., Grad. Univ. Of Chinese Acad. Of Sci., Chengdu, China
Abstract :
In order to overcome the limitations of traditional focusing function, the reasons why traditional approach lower the focusing precision are analyzed, and a theory based on curve fitting and probabilistic model is proposed. This algorithm can effectively improve the limitations that one focusing function is applicable to one type of image only, so that the classical image definition evaluation function are able to determine the focal position. We accomplished some experiments based on the images obtained from the CCD of the lab. Experimental results show that the proposed focusing algorithm based on definition evaluation function has an excellent focusing performance, good noise immunity and practical applications.
Keywords :
curve fitting; image processing; probability; curve fitting; focal position; focusing function; focusing precision; image definition evaluation function; improved focusing algorithm; noise immunity; probabilistic model; Charge coupled devices; Curve fitting; Focusing; Image sequences; Interference; Noise; Auto Focus; focusing algorithm; image definition evaluation;
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
DOI :
10.1109/AIMSEC.2011.6009938