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Single Color Image Super Resolution

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Reji A.P., Tessamma Thomas

Reji A.P. and Tessamma Thomas. Single Color Image Super Resolution. International Journal of Computer Applications 183(31):13-17, October 2021. BibTeX

	author = {Reji A.P. and Tessamma Thomas},
	title = {Single Color Image Super Resolution},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2021},
	volume = {183},
	number = {31},
	month = {Oct},
	year = {2021},
	issn = {0975-8887},
	pages = {13-17},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2021921698},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


The single image super-resolution refers to the process of recovering missing high-resolution details so as to reconstruct a high resolution image(HR) from a single low resolution image (LR). Correspondences between low and high resolution image patches are learned from a database of low and high resolution image pairs, and then applied to a new low-resolution image to recover its most likely high-resolution version. In this paper color image super resolution method is implemented using critically sampled directionlet transform. In this method color image in RGB format is converted to YCbCr format. The luminance component Y alone is super resolved and other two components are interpolated using standard methods. At the end the YCbCr format is converted back to RGB format.


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Directionlet, anisotropic, super resolution, Colour, RGB