On Creating Reference Data for Performance Analysis in Image Processing

This thesis investigates methods for the creation of reference datasets for image processing, especially for the dense correspondence problem. Three types of reference data can be identified: Real datasets with dense ground truth, real datasets with sparse or missing ground truth and synthetic datasets. For the creation of real datasets with ground truth a existing method based on depth map fusion was evaluated. The described method is especially suited for creating large amounts of reference data with known accuracy. The creation of reference datasets with missing ground truth was examined on the example of multiple datasets for the automotive industry. The data was used succesfully for verification and evaluation by multiple image processing projects. Finally, it was investigated how methods from computer graphics can be used for creating synthetic reference datasets. Especially the creation of photorealistic image sequences using global illumination has been examined for the task of evaluating algorithms. The results show that while such sequences can be used for evaluation, their creation is hindered by practicallity problems. As an application example, a new simulation method for Time-of-Flight depth cameras which can simulate all relevant error sources of these systems was developed

MDia and POTS - The Munich Difference Imaging Analysis for the pre-OmegaTranS Project

We describe the Munich Difference Imaging Analysis pipeline that we developed and implemented in the framework of the Astro-WISE package to automatically measure high precision light curves of a large number of stellar objects using the difference imaging approach. Combined with programs to detect time variability, this software can be used to search for planetary systems or binary stars with the transit method and for variable stars of different kinds. As a first scientific application, we discuss the data reduction and analysis performed with Astro-WISE on the pre-OmegaTranS data set, that we collected during a monitoring campaign of a dense stellar field with the Wide Field Imager at the ESO 2.2m telescope.Comment: 10 pages, 5 figures, accepted for publication in topical issue of Experimental Astronomy on Astro-WISE information syste

The Application of the Montage Image Mosaic Engine To The Visualization Of Astronomical Images

The Montage Image Mosaic Engine was designed as a scalable toolkit, written in C for performance and portability across *nix platforms, that assembles FITS images into mosaics. The code is freely available and has been widely used in the astronomy and IT communities for research, product generation and for developing next-generation cyber-infrastructure. Recently, it has begun to finding applicability in the field of visualization. This has come about because the toolkit design allows easy integration into scalable systems that process data for subsequent visualization in a browser or client. And it includes a visualization tool suitable for automation and for integration into Python: mViewer creates, with a single command, complex multi-color images overlaid with coordinate displays, labels, and observation footprints, and includes an adaptive image histogram equalization method that preserves the structure of a stretched image over its dynamic range. The Montage toolkit contains functionality originally developed to support the creation and management of mosaics but which also offers value to visualization: a background rectification algorithm that reveals the faint structure in an image; and tools for creating cutout and down-sampled versions of large images. Version 5 of Montage offers support for visualizing data written in HEALPix sky-tessellation scheme, and functionality for processing and organizing images to comply with the TOAST sky-tessellation scheme required for consumption by the World Wide Telescope (WWT). Four online tutorials enable readers to reproduce and extend all the visualizations presented in this paper.Comment: 16 pages, 9 figures; accepted for publication in the PASP Special Focus Issue: Techniques and Methods for Astrophysical Data Visualizatio

Inviwo -- A Visualization System with Usage Abstraction Levels

The complexity of today's visualization applications demands specific visualization systems tailored for the development of these applications. Frequently, such systems utilize levels of abstraction to improve the application development process, for instance by providing a data flow network editor. Unfortunately, these abstractions result in several issues, which need to be circumvented through an abstraction-centered system design. Often, a high level of abstraction hides low level details, which makes it difficult to directly access the underlying computing platform, which would be important to achieve an optimal performance. Therefore, we propose a layer structure developed for modern and sustainable visualization systems allowing developers to interact with all contained abstraction levels. We refer to this interaction capabilities as usage abstraction levels, since we target application developers with various levels of experience. We formulate the requirements for such a system, derive the desired architecture, and present how the concepts have been exemplary realized within the Inviwo visualization system. Furthermore, we address several specific challenges that arise during the realization of such a layered architecture, such as communication between different computing platforms, performance centered encapsulation, as well as layer-independent development by supporting cross layer documentation and debugging capabilities