Generalized Image Acquisition and Analysis

On Plenoptic Multiplexing and Reconstruction

Photography has been striving to capture an ever increasing amount of visual information in a single image. Digital sensors, however, are limited to recording a small subset of the desired information at each pixel. A common approach to overcoming the limitations of sensing hardware is the optical multiplexing of high-dimensional data into a photograph. While this is a well-studied topic for imaging with color filter arrays, we develop a mathematical framework that generalizes multiplexed imaging to all dimensions of the plenoptic function. This framework unifies a wide variety of existing approaches to analyze and reconstruct multiplexed data in either the spatial or the frequency domain. We demonstrate many practical applications of our framework including high-quality light field reconstruction, the first comparative noise analysis of light field attenuation masks, and an analysis of aliasing in multiplexing applications.


A Mathematical Model and Calibration Procedure for Galvanometric Laser Scanning Systems

Alkhazur Manakov, Hans-Peter Seidel, Ivo Ihrke
In: Vision, Modeling, and Visualization (VMV 2011)


Laser galvanometric scanning systems are commonly used in various fields such as three dimensional scanning, medical imaging, material processing, measurement devices and laser display systems. The systems of such kind suffer from distortions. On top of that they do not have a center of projection, which makes it impossible to use common projector calibration procedures. The paper presents a novel mathematical model to predict the image distortions caused by galvanometric mirror scanning systems. In addition, we describe a calibration procedure for recovering its intrinsic and extrinsic parameters.


author = {Alkhazur Manakov and Hans-Peter Seidel and Ivo Ihrke},
title = "{A Mathematical Model and Calibration Procedure for Galvanometric Laser Scanning Systems}",
booktitle = {Proceedings of VMV},
pages = "207--214",
year = {2011},
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