In this paper, a transparent flow surface reconstruction based on wave front distortion is investigated. A camera lens is used to focus the image formed by the micro-lens array to the camera imaging plane. The irradiance of the captured image is transformed to frequency spectrum and then the x and y spatial components are separated. A rigid spatial translation followed by low pass filtering yields a single frequency component of the image intensity. Index of refraction is estimated from the inverse Fourier transform of the spatial frequency spectrum of the irradiance. The proposed method is evaluated with synthetic data of a randomly generated index of refraction value and used to visualize a fuel injection volumetric data.
This paper discusses a method to reconstruct a transparent ow surface from single camera shot with the aid of a Micro-lens array. An intentionally prepared high frequency background which is placed behind the refractive flow is captured and a curl-free optical flow algorithm is applied between pairs of images taken by different micro-lenses. The computed raw optical ow vector is a blend of motion parallax and background deformation vector due to the underlying flow. Subtracting the motion parallax, which is obtained by calibration, from the total op- optical flow vector yields the background deformation vector. The deflection vectors on each images are used to reconstruct the flow profile. A synthetic data set of fuel injection was used to evaluate the accuracy of the proposed algorithm and good agreement was achieved between the test and reconstructed data. Finally, real light field data of hot air created by a lighter flame is used to reconstruct and show a hot air plume surface.
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