IMAGE QUALITY CHARACTERISTICS IN SUPER-RESOLUTION METHODS

Authors

DOI:

https://doi.org/10.30890/2567-5273.2024-35-00-022

Keywords:

image processing, raster graphics, generative neural network, bicubic interpolation, super-resolution, quality enhancement, image characteristics

Abstract

The article addresses the current issue of assessing the quality of raster images in the context of Super-Resolution methods. The main characteristics affecting the quality of raster images are identified, including factors that lead to its degradation, s

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References

Wang, Zhou; Bovik, A.C.; Sheikh, H.R.; Simoncelli, E.P. (2004-04-01). "Image quality assessment: from error visibility to structural similarity". IEEE Transactions on Image Processing. 13 (4): 600–612.

Bian Yang. Block Mean Value Based Image Perceptual Hashing (2006). Second International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2006), Pasadena, California, USA, December 18-20, 2006, Proceedings

Zhou Wang; Alan C. Bovik (2006). Modern Image Quality Assessment. pp. 11–15.

Goodfellow, Ian; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua (2014). Generative Adversarial Nets. Proceedings of the International Conference on Neural Information Processing Systems (NIPS 2014). pp. 2672–2680.

B. M. Ngocho, E. Mwangi, "Single image super resolution with improved wavelet interpolation and iterative back-projection", IOSR Journal of VLSI and Signal Processing, vol. 5, no. 6, pp. 16-24, Nov – Dec 2015.

Published

2024-10-30

How to Cite

Грубнік, О., & Бушин, І. (2024). IMAGE QUALITY CHARACTERISTICS IN SUPER-RESOLUTION METHODS. Modern Engineering and Innovative Technologies, 1(35-01), 119–123. https://doi.org/10.30890/2567-5273.2024-35-00-022

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Articles