Automatic construction of single frame super-resolution using Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7650

@InProceedings{Natsui:2013:IWCIA,

• author = "Yusuke Natsui and Tomoharu Nagao",
• booktitle = "Sixth IEEE International Workshop on Computational Intelligence Applications (IWCIA 2013)",
• title = "Automatic construction of single frame super-resolution using Cartesian Genetic Programming",
• year = "2013",
• month = "13 " # jul,
• pages = "149--154",
• keywords = "genetic algorithms, genetic programming, Cartesian genetic programming, graphics processing units, image resolution, parallel processing, CGP, GPU, HR image, LR image, computational cost reduction, graphics processing unit, high-resolution image, image generation, image quality, low-resolution image, parallel processing, pixel values, single frame super-resolution method, Buildings, Computational efficiency, Face, Graphics processing units, Image resolution, PSNR, Training, Single Frame Super-Resolution",
• DOI = "doi:10.1109/IWCIA.2013.6624803",
• ISSN = "1883-3977",
• abstract = "In this paper, we propose a single-frame Super-Resolution (SR) method using Cartesian Genetic Programming (CGP). Our method is to learn relationship of pixel values between high-resolution (HR) image and low-resolution (LR) image using CGP, and we construct a SR rule of generating SR image from a LR input image. A single pixel and its neighbour pixels of the LR input image are set to the inputs of CGP. And then, pixel values of the SR image are obtained from the calculated outputs of CGP. Therefore, the SR image is generated from the LR input image. In addition, multiple CGP can improve the quality of SR image. Because our method is to perform for each pixel independently, our method is suitable to parallel processing. Therefore, in order to reduce computational cost, we use parallel processing with graphics processing unit (GPU). Experimental results show efficient processing is constructed. Our method is little less quality than one conventional work which is the state of the art method on image quality, however to perform overwhelmingly faster than the conventional work. We can construct fast and accurate single-frame super-resolution.",
• notes = "Also known as \cite{6624803}",

}

Genetic Programming entries for Yusuke Natsui Tomoharu Nagao

Citations