Depth from Focus with Adaptive Focus Measure Using Gray Level Variance Based on Poisson Distribution

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  • ポアソン分布に基づく輝度偏差を用いた適用的合焦評価によるDepth from Focus法
  • ポアソン ブンプ ニ モトズク キド ヘンサ オ モチイタ テキヨウテキゴウショウヒョウカ ニ ヨル Depth from Focusホウ

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Abstract

We aim to estimate the depth of microscopic objects by image processing, and describe a depth-from-focus (DFF) method that uses multiple images taken with different focus lengths. DFF methods usually estimate the depth at a pixel by evaluating image sharpness among the images, but they are not good at handling texture-less regions and regions including strong edges because image sharpness is not properly obtained in such regions, which results in accuracy deterioration. To address the problems, we focus on a relation between the luminance of a target pixel and neighboring pixels’ mean value, and propose a sharpness measurement method under the assumption that the relation follows Poisson distribution. In addition, our method uses multiple window sizes when taking into account the neighboring pixels to improve accuracy, and integrates evaluated focus measures by using a DFF algorithm of Fommer et al. We show the effectiveness of our method through numerical results using simulation images and quantitative results using actual images.

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