Wavelet and PCA-based approach for 3D shape recovery from image focus

Muhammad Tariq Mahmood; Seongo Shim; Tae-Sun Choi

doi:10.1117/12.798214

15 September 2008 Wavelet and PCA-based approach for 3D shape recovery from image focus

Muhammad Tariq Mahmood, Seongo Shim, Tae-Sun Choi

Proceedings Volume 7073, Applications of Digital Image Processing XXXI; 70731S (2008) https://doi.org/10.1117/12.798214
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

Abstract

This paper introduces a new approach for 3D shape recovery based on Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). Contrary to computing focus quality locally by summing all values in a 2D or 3D window obtained after applying a focus measure, a vector consisting of seven neighboring pixels is populated for each pixel in the image volume. Each vector in the sequence is decomposed by using DWT and then PCA is applied on the energies of detailed coefficients to transform the data into eigenspace. The first feature, as it contains maximum variation, is employed to compute the depth. Though DWT and PCA are both computationally expensive transformations, the reduced data elements and algorithm iterations have made the proposed method efficient. The new approach was experimented and its performance was compared with other methods by using synthetic and real image sequences. The evaluation is gauged on the basis of unimodality, monotonicity and resolution of the focus curve. Two other global statistical metrics Root Mean Square Error (RMSE) and correlation have also been applied for synthetic image sequence. Experimental results demonstrate the effectiveness and the robustness of the new method.

Citation Download Citation

Muhammad Tariq Mahmood, Seongo Shim, and Tae-Sun Choi "Wavelet and PCA-based approach for 3D shape recovery from image focus", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70731S (15 September 2008); https://doi.org/10.1117/12.798214

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