Use of Flawed and Ideal Image Pairs to Drive Filter Creation by Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{conf/dphoto/SridharDE16,

• title = "Use of Flawed and Ideal Image Pairs to Drive Filter Creation by Genetic Programming",
• author = "Subash Marri Sridhar and Henry G. Dietz and Paul Selegue Eberhart",
• editor = "Jackson Roland and Radka Tezaur and Dietmar Wueller",
• publisher = "Ingenta",
• year = "2016",
• volume = "2016",
• number = "18",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2470-1173",
• URL = "http://www.ingentaconnect.com/content/ist/ei/2016/00002016/00000018/art00023",
• DOI = "doi:10.2352/ISSN.2470-1173.2016.18.DPMI-016",
• bibdate = "2016-07-05",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/dphoto/dphoto2016.html#SridharDE16",
• booktitle = "Digital Photography and Mobile Imaging {XII}, San Francisco, California, {USA}, February 14-18, 2016",
• URL = "http://ist.publisher.ingentaconnect.com/content/ist/ei/2016/00002016/00000018",
• abstract = "Traditional image enhancement techniques improve images by applying a series of filters, each of which repairs a specific type of flaw, but most modern digital cameras produce images with a variety of subtle interacting defects. Sequential repair is slow, and the interactions limit the effectiveness. This paper describes a fundamentally different approach in which a single filter is created to repair the potentially myriad interacting defects associated with a particular camera configuration and set of exposure parameters. Genetic programming (GP) is used to automatically evolve a filter algorithm that will convert flawed images into images minimally differing at the pixel level from the corresponding provided ideal images. For example, the flawed images might be shot at a high ISO and the ideal ones might be the exact same static scenes, aligned at the pixel level, but shot at a low ISO using appropriately longer exposure times. Just as easily, the flawed images might be technically well corrected, while the ideal ones were manually-edited to adjust and smooth skin tones, sharpen hair, enhance shadow regions, et. The custom-coded parallel GP, its performance, and performance of the generated filters is discussed with an example.",
• notes = "Published in Electronic Imaging science and technology",

}

Genetic Programming entries for Subash Marri Sridhar Henry G Dietz Paul Selegue Eberhart

Citations