WAVELET ANALYSIS BASED IMAGE SUPER RESOLUTION
Abstract
The increase in demand and performance of personal computing digital image processing is widely being used in many applications. Digital image process has advantage in term of cost, speed and flexibility. The objective is to extract information from the scene is being viewed. Image resolution describes the amount of information contained by images. Resolution has been frequently referred as an important aspect of an image. Images are being processed in order to obtain more enhanced resolution. One of the commonly used techniques for image resolution enhancement is Interpolation. In this work, an image resolution enhancement technique has been proposed which generates sharper high resolution image. The proposed technique uses DWT to decompose a low resolution image into different subbands. Then the three high frequency sub-band images have been interpolated using bi-cubic interpolation. The high frequency sub-bands obtained by SWT of the input image are being incremented into the interpolated high frequency sub-bands in order to correct the estimated coefficients. In parallel, the input image is also interpolated separately. Although the time and frequency resolution problems are results of a physical phenomenon (the Eisenberg uncertainty principle) and exist regardless of the transform used, it is possible to analyze any signal by using an alternative approach called the multi resolution analysis (MRA)
References
[25] Woo D.H., Eom I.K. and Kim Y.S., “Image Interpolation based on interscale dependency in wavelet domain”, Proc. ICIP „04, vol. 3, 16871690, Oct. 2004. [26] Kim J.H., Lee S.H. and Cho N.I., “Bayesian Image Interpolation Based on the Learning and Estimation of Higher Band Wavelet Coefficients”, Proc. ICIP ‟06, Oct. 2006. [27] Temizel A. and Vlachos T., “Wavelet Domain Image Resolution Enhancement”, IEE Proceedings Vision, Image and Signal Proc., vol. 153, no. 1, pp 25-30, Feb. 2006. [28] Li X. and Orchard M.T., “New edge-directed interpolation”, IEEE Tr. Image Proc., Vol. 10, No. 10, pp. 1521-1527, Oct. 2001.
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