<p>Digital images and videos used in the investigation of a crime often undergo several concurrent enhancement operations for improved analysis by humans or automated systems. When applying multiple image processing techniques to an image, the order and method in which processes are applied can have a profound impact on the result. However, the effect that one enhancement algorithm will have when applied in conjunction with another is not always obvious. When applied incorrectly, at best, there will be a negative impact to the amount of information that can be extracted from an image. At worst, the information contained in a processed image could be misrepresented. This thesis proposes a tool independent workflow for forensic image enhancement with a strong emphasis on an order of operations that maximizes the efficacy of each enhancement technique while observing the responsibilities and best practices of the forensic science community. This work will be useful for developing an understanding of common image enhancement techniques, understanding how these techniques relate to forensic science, and aiding in the creation of quality assurance standards for forensic image enhancement. Chapter 1 gives an introduction to image enhancement and discusses its role in forensic science and litigation. Chapter 2 summarizes the digital image creation process and its relationship to the human visual system. Chapter 3 reviews the most commonly used image enhancement techniques, including their theoretical background, strengths, and limitations. Chapter 4 introduces a framework for image enhancement and the rationale behind it through a series of practical examples.
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:1605105 |
| Date | 16 December 2015 |
| Creators | Ledesma, Spencer Aguila |
| Publisher | University of Colorado at Denver |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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