The Journal of The Institute of Image Information and Television Engineers

This paper presents a novel texture-mapping method, called harmonized texture mapping (HTM), for reducing the blurring and ghosting artifacts that are created by most existing visualization methods which do not consider the inaccuracy of a generated 3D shape and camera parameters. HTM can significantly reduce the occurrence of artifacts by dynamically adjusting textures generated from multi-viewpoint images in accordance with both textural features of the images and geometrical features of the generated 3D shape. The performance of HTM is evaluated by quantitative and qualitative experiments using several 3D video sequences.

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We present a way of using a computer simulation to reconstruct gray-level images from computer-generated Fresnel holograms (Fresnel CGHs) using a two-dimensional (2D) image as an object. The interference fringes formed with spherical object waves emitting from 2D-image pixels and a plane reference wave were recorded as the sum of Fresnel zone plates at a CGH plane. It is assumed that the amplitude of the object wave is proportional to the pixel intensity of the 2D image. Reconstructed images from the Fresnel CGH are obtained by applying the fast Fourier transform algorithm to the Fresnel-Kirchhoff diffraction integral. The simulations were executed by changing parameters such as a bit number for CGH data recordings and a sampling interval of the interference fringes at the CGH plane, and some simulation results are presented; recording data with a resolution of 5 or more bits appears to be the best way to construct high-quality images.

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We propose a method that can reconstruct both facial poses and the facial shape from freehand multi-viewpoint snapshots. This method is based on Active Shape Models (ASM), which is a technique that uses a facial shape database. Most ASM methods require image in which the facial pose is known, but our method does not require this information. First, we chose an initial shape by selecting the model from the database which is most similar to the input images. Then, we improve the model by morphing it to better fit the input images. Next, we estimate the pose of the face using the morphed model. Finally we repeat the process, improving both the facial shape and the facial pose until the error between the input and the computed result is minimized. Through experimentation, we show that our method reconstructs the facial shape within 3.5mm of the ground truth.

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We propose a dynamic range extension method for CMOS imagers with an in-pixel lateral overflow structure, in which one of active and passive readout schemes is selected at each pixel on the basis of the illumination. For a high illumination, the charges stored in both photodiode and area-effective MOS capacitor as an overflow capacitor in a pixel are read with high linearity by a charge amplifier at each column to extend the range of the readable voltage. The column circuit area is suppressed and row-wise pixels are accessed by sharing the pixel control signals and the column amplifier between two readout modes. We also describe an image reproduction scheme that makes use of electric calibration from a pixel-wise mixed-mode image. The signal-to-noise ratio of the scheme is discussed. Preliminary experiments with a 128 x96-pixel prototype imager fabricated in 0.35μm CMOS technology showed an extension of the dynamic range of 18.5 dB (72.8 dB in total) and offline wide-dynamic-range image reproduction. Optimizing of the capacitances in the pixels and the column amplifier and reducing the amount of noise in the column amplifiers will provide a total dynamic range of around 120dB.

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