A comparative evaluation of super – resolution methods on color images

Erbay, Fulya
In this thesis, it is proposed to get the high definition color images by using super – resolution algorithms. Resolution enhancement of RGB, HSV and YIQ color domain images is presented. In this study, three solution methods are presented to improve the resolution of HSV color domain images. These solution methods are suggested to beat the color artifacts on super resolution image and decrease the computational complexity in HSV domain applications. PSNR values are measured and compared with the results of other two color domain experiments. In RGB color space, super – resolution algorithms are applied three color channels (R, G, B) separately and PSNR values are measured. In YIQ color domain, only Y channel is processed with super resolution algorithms because Y channel is luminance component of the image and it is the most important channel to improve the resolution of the image in YIQ color domain. Also, the third solution method suggested for HSV color domain offers applying super resolution algorithm to only value channel. Hence, value channel carry brightness data of the image. The results are compared with the YIQ color domain experiments. During the experiments, four different super resolution algorithms are used that are Direct Addition, MAP, POCS and IBP. Although, these methods are widely used reconstruction of monochrome images, here they are used for resolution enhancement of color images. Color super resolution performances of these algorithms are tested.
Citation Formats
F. Erbay, “A comparative evaluation of super – resolution methods on color images,” M.S. - Master of Science, Middle East Technical University, 2011.