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Telecommunications and Radio Engineering
SJR: 0.202 SNIP: 0.2 CiteScore™: 0.23

ISSN Druckformat: 0040-2508
ISSN Online: 1943-6009

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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v72.i19.80
pages 1803-1820

IMAGE RESOLUTION ENHANCEMENT USING EDGE EXTRACTION, SPARSE REPRESENTATION AND INTERPOLATION IN WAVELET DOMAIN

H. Chavez-Roman
Instituto Politécnico Nacional, Mexico-city, Mexico
Gonzalo Duchen-Sanchez
SEPIESIME Culhuacan, National Polytechnic Institute (IPN) Av. Santa Ana No. 1000, C.P. 04430 Mexico D.F. MEXICO
Victor Filippovich Kravchenko
Kotelnikov Institute of Radio Engineering and Electronics, Russian Academy of Sciences, 11-7, Mokhovaya St., Moscow 125009, Russia; Bauman Moscow State Technical University, 5, Vtoraya Baumanskaya St., Moscow 105005 Russia; Scientific and Technological Center of Unique Instrumentation, Russian Academy of Sciences, 15, Butlerova St., Moscow 117342, Russia
Volodymyr Ponomaryov
Instituto Politécnico Nacional, Mexico-city, Mexico

ABSTRAKT

Over the past few years, high-resolutions (HR) are desirable or essential, e.g., in online video systems, and therefore much has been done to achieve an image of higher resolution from the corresponding low resolution (LR) images. This procedure of recover or rebuild is called single image super-resolution (SR). This study addresses the problem of generating a SR image from a LR input image in the wavelet domain. In order to achieve a sharper image, an intermediate stage for estimating the high-frequency (HF) sub-bands has been proposed. It includes an edge preservation procedure and mutual interpolation between the input LR image and the HF sub-band images performed via the discrete wavelet transform (DWT). Sparse mixing weights are calculated over blocks of coefficients in an image, providing a sparse signal representation in the LR image. All sub-band images are used to generate the new HR image employing the inverse DWT. Experimental results have shown that the proposed approach outperforms existing methods in terms of objective criteria and subjective perception via human visual system, improving the image resolution.


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