A Spectral Radius Based Evaluation Function for Automatic Focusing

Curves generated by traditional evaluating functions contain large amount of local extremums, easily leading to focal-plane misjudgments. We propose a new clarity evaluation method based on spectral radius. The spatial information is converted into frequency domain by Discrete Cosine Transformation, then a sector that contains more than 99 percent of the total spectrum energy is extracted, and the radius of this sector is employed to estimate the degree of clarity of current image. Since the scope of spectral radius is steady and limited to image size, it provides effective reference for selection of lower limit of spectral radius which is utilized to avoid local fluctuation and maintain the unimodality of evaluation curves. The experimental results demonstrate that the spectral radius based evaluation method forms curves with fewer local extremums and better robustness.