Iterative spatial domain 2-D signal decomposition for effectual image up-scaling
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Iterative spatial domain 2-D signal decomposition for effectual image up-scaling Aditya Acharya 1 & Sukadev Meher 2 Received: 25 May 2020 / Revised: 8 September 2020 / Accepted: 17 September 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
Image up-scaling employs various polynomial interpolation schemes for their reduced computational complexity and suitability for various real-time applications. However, they give blurring artifacts in up-scaled images due to the loss of high frequency (HF) information. Likewise, most of the other edge directed and transform domain interpolation schemes available in the literature though produce lesser blurring as compared to polynomial interpolation schemes but are computationally more complex. To overcome these problems, an iterative spatial domain 2-D signal decomposition technique is proposed. It is meant for extracting the very high frequency (VHF) information from a low resolution (LR) image. The VHF information is obtained by performing the signal decomposition for an estimated number of iterations. Subsequently, the superimposition of this VHF extract with the low resolution image prior to image up-scaling reduces the blurring in its up-scaled counterpart. Since the degradation of higher order sub-band information such as HF and VHF is more than the low and medium frequency information during an up-scaling process, restoration of the most degraded VHF sub-band information would produce much lesser blurring. Simulation results reveal that the proposed scheme gives better performance than many of the existing schemes in terms of objective and subjective measures. Keywords Up-scaling . Interpolation . de-blurring . Signal decomposition . Imagepre-processing . Filter bank
* Aditya Acharya [email protected] Sukadev Meher [email protected]
1
Department of Electronics and Communication Engg, Silicon Institute of Technology Bhubaneswar, Bhubaneswar 751024, India
2
Department of Electronics and Communication Engg, National Institute of Technology Rourkela, Rourkela 769008, India
Multimedia Tools and Applications
1 Introduction Image up-scaling is a topic of great interest in recent years and is used for generating a high resolution (HR) image from a low resolution (LR) image data. An efficient image up-scaling scheme must preserve the high frequency information, texture, geometrical regularities and smoothness of the original LR image while producing its corresponding HR counterpart. The most common application of image up-scaling is to provide an enhanced visual effect after resizing a digital image for display and printing [7]. Image up-scaling through interpolation is the process of estimating the intermediate values of a spatially continuous image from a set of its discrete samples. It typically estimates an unknown pixel value within a neighborhood from the known pixel neighbors. Typically, the interpolated value at a particular location is computed by the weighted average or convolution of the neighboring image samples resulti
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