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Analysis of Various Color Space Models on Effective Single Image Super Resolution

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Book cover Intelligent Systems Technologies and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 384))

Abstract

Color models are used for facilitating the specification of colors in a standard way. A suitable color model is associated with every application based on color space. This paper mainly focuses on the analysis of effectiveness of different color models on single image scale-up problems. Single image scale-up aims in the recovery of original image, where the input image is a blurred and down- scaled version of the original one. In order to identify the effect of different color models on scale-up of single image applications, the experiment is performed with the single image scale-up algorithm on standard image database. The performance of different color models (YCbCr, YCoCg, HSV, YUV, CIE XYZ, Photo YCC, CMYK, YIQ, CIE Lab, YPbPr) are measured by quality metric called Peak Signal to Noise Ratio (PSNR). The experimental results based on the calculated PSNR values prove that YCbCr and CMYK color models give effective results in single image scale-up application when compared with the other available color models.

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Correspondence to Neethu John .

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John, N., Viswanath, A., Sowmya, V., Soman, K.P. (2016). Analysis of Various Color Space Models on Effective Single Image Super Resolution. In: Berretti, S., Thampi, S., Srivastava, P. (eds) Intelligent Systems Technologies and Applications. Advances in Intelligent Systems and Computing, vol 384. Springer, Cham. https://doi.org/10.1007/978-3-319-23036-8_46

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  • DOI: https://doi.org/10.1007/978-3-319-23036-8_46

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