Global motion based video super-resolution reconstruction using discrete wavelet transform

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dc.contributor.authorWitwit, Wasnaa
dc.contributor.authorZhao, Yifan
dc.contributor.authorJenkins, Karl W.
dc.contributor.authorAddepalli, Sri
dc.date.accessioned2018-04-13T08:40:06Z
dc.date.available2018-04-13T08:40:06Z
dc.date.issued2018-04-11
dc.description.abstractDifferent from the existing super-resolution (SR) reconstruction approaches working under either the frequency-domain or the spatial- domain, this paper proposes an improved video SR approach based on both frequency and spatial-domains to improve the spatial resolution and recover the noiseless high-frequency components of the observed noisy low-resolution video sequences with global motion. An iterative planar motion estimation algorithm followed by a structure-adaptive normalised convolution reconstruction method are applied to produce the estimated low-frequency sub-band. The discrete wavelet transform process is employed to decompose the input low-resolution reference frame into four sub-bands, and then the new edge-directed interpolation method is used to interpolate each of the high-frequency sub-bands. The novelty of this algorithm is the introduction and integration of a nonlinear soft thresholding process to filter the estimated high-frequency sub-bands in order to better preserve the edges and remove potential noise. Another novelty of this algorithm is to provide flexibility with various motion levels, noise levels, wavelet functions, and the number of used low-resolution frames. The performance of the proposed method has been tested on three well-known videos. Both visual and quantitative results demonstrate the high performance and improved flexibility of the proposed technique over the conventional interpolation and the state-of-the-art video SR techniques in the wavelet- domain.en_UK
dc.identifier.citationWitwit, W., Zhao, Y., Jenkins, K. et al. Global motion based video super-resolution reconstruction using discrete wavelet transform. Multimed Tools Applications, October 2018, Volume 77, Issue 20, pp 27641–27660en_UK
dc.identifier.issn1380-7501
dc.identifier.urihttps://doi.org/10.1007/s11042-018-5941-5
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/13142
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectImage enhancementen_UK
dc.subjectImage registrationen_UK
dc.subjectImage reconstructionen_UK
dc.titleGlobal motion based video super-resolution reconstruction using discrete wavelet transformen_UK
dc.typeArticleen_UK

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