Estimating best focused points through similarity matrix

Muhammad Tariq Mahmood; Tae-Sun Choi

doi:10.1117/12.827226

2 September 2009 Estimating best focused points through similarity matrix

Proceedings Volume 7443, Applications of Digital Image Processing XXXII; 74432C (2009) https://doi.org/10.1117/12.827226
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

Shape from focus (SFF) is a passive optical method for 3D shape recovery, which has numerous applications in machine vision, range segmentation, and video microscopy. This paper introduces a new algorithm for shape from focus (SFF) based on multidimensional scaling (MDS) analysis. In contrast to the conventional focus measures operators, a three dimensional neighborhood, enabling to capture the effect of pixels from previous as well as next frames on focus value, is considered for each pixel in the image volume. A similarity matrix is computed using Euclidean metric for the sequence of these 3D neighborhoods corresponding to each object point. This matrix is then provided as input to MDS algorithm. The monotonic regression is applied which computes the fitness of the approximated configuration by using stress function as the criterion for the fitness. The energy of the components in lower dimensions is employed to compute the best focused point and its corresponding depth. The proposed method is experimented using synthetic and real image sequences. The evaluation is gauged on the basis of unimodality and monotonicity of the focus curve. Experimental results have demonstrated the effectiveness of the new method.

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Muhammad Tariq Mahmood and Tae-Sun Choi "Estimating best focused points through similarity matrix", Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 74432C (2 September 2009); https://doi.org/10.1117/12.827226

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KEYWORDS

3D image processing

Optical filters

3D modeling

Cameras

Control systems

Point spread functions

Image processing algorithms and systems

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