Genetic algorithm optimization of superresolution parameters

Superresolution is the process of producing a high resolution image from a collection of low resolution images. This process has potential application in a wide spectrum of fields in which navigation, surveillance, and observation are important, yet in which target images have limited resolution. There have been numerous methods proposed and developed to implement superresolution, each with its own advantages and limitations. However, there is no standard method or software for superresolution. In this paper a genetic algorithm solution for determining the registration and point spread function (PSF) parameters for superresolution is proposed and implemented, and a superresolved image is generated using genetic algorithm optimization of an existing superresolution method. Categories and Subject Descriptors I.4.0 [Image Processing and Computer Vision]: General – Image processing software. General Terms Algorithms, Measurement, Performance. Keywords Genetic Algorithms, Superresolution...

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Barry Ahrens
• Keywords: GECCO 2005, Genetic Algorithms, Point Spread Function, Resolution Images