Image clarity evaluation algorithm based on region weighting
Aiming at the problems of low sensitivity and many local extreme points of the clarity evaluation function during the focusing process of the photoelectric imaging system.This paper proposes an image clarity evaluation algorithm based on regional weighting.First,the algorithm adopts a threshold based on the traditional Laplacian evaluation function to improve the anti-noise and the ratio of clarity.Then,the algorithm also uses the image gradient map to calculate the regional clarity weighting factor which can optimize the variance of flat part of focusing curve.Experimental results show that compared with the most traditional clarity evaluation functions,the clarity ratio of this algorithm is increased by about 2.7 times、the sensitivity increases by about 1.9 times and the variance of flat part of focusing curve can be reduced to 1/6 of the traditional Laplacian evaluation function.In general,this algorithm has the advantages of high clarity ratio and sensitivity、low variance of flat part of focusing curve and has better evaluation performance when the image content is complex.
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