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.

Teaching

Parallel Visual Computing

Seminar in winter term 2012/13

Lecturers: Ivo Ihrke, Tobias Ritschel, Mario Fritz

General Information

Course webpage

When: 2012, Oct. 18th to 2013, Jan. 31st
Where: E1.7 room 0.01
Registration for mailing list: send email to Ivo Ihrke (lastname@mmci.uni-saarland.de)

Overview:

This seminar covers the hands-on use of parallel hardware (CPUs and GPUs) for visual computing, i.e.,

  • Computer vision (e.g., from simple image operations to classification)
  • Computer graphics (e.g., advanced shading)
  • Scientific computing (e.g., equation solving)

The target audience are students in computer science or related fields. Good C++ programming skills, basic knowledge about 3D geometry, image processing, and computer graphics are required. This seminar will be based on hands-on parallel programming:

  • Every one week, a tutor will present a problem with an interesting parallel solution.
  • On the same day there will be a programming assignment on the topic.
  • Teams of two people will work on this assignment
  • Every team demos their solution and we discuss

FAQ:


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