Estimating the amount of defocus through a wavelet transform approach

Authors:
Jinlong Lin;Chao Zhang;Qingyun Shi
Affiliations:
Center for Information Science, Room 306, Building 18, Wei Xiuyan, Peking University, Beijing 100871, PR China;Center for Information Science, Room 306, Building 18, Wei Xiuyan, Peking University, Beijing 100871, PR China;Center for Information Science, Room 306, Building 18, Wei Xiuyan, Peking University, Beijing 100871, PR China
Venue:
Pattern Recognition Letters
Year:
2004

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Abstract

This paper presents a new technique for defocus estimation of a captured image. In our method, a ratio of the wavelet coefficients of high frequency correspond to a same image point at two different levels is used. For an edge point, it is shown that the ratio is related to the amount of defocus. Let α be the ratio of wavelet coefficients at the first level to that at the second level. The value of α decreases as the amount of defocus increase. In our experiments of iris image analysis, when α is larger than 0.5 the number of feature points in an image almost remain constant. It means that the image is little defocused and available for image recognition. Compared with Fourier methods, this technique is more robust. In addition, this method is fast enough to be used in auto-focus system for tracking moving objects.