Image Resolution Enhancement using DWT and Edge Extraction
IT Skills Show & International Conference on Advancements in Computing Resources, (SSICACR-2017) 15 and 16 February 2017, Alagappa University, Karaikudi, Tamil Nadu, India. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)
Download this PDF format
Abstract
Image resolution enhancement is a method to improve the quality of an image and it is a preprocess step for various image processing applications. This paper presents a technique to improve the resolution of the low quality images. In the proposed method Discrete wavelet transform (DWT) is used to decompose the input image in to different subbands. To further capture the high frequency details from the high frequency subbandsHaar wavelet transform is used. Edges are extracted from the sub-images to preserve the edge detail effectively. Then the High frequency subbands are interpolated. Finally inverse Haar and inverse DWT is performed to get high resolution image.
References
[1] XiaominWu,JiulunFan,JianXu,YanziWangG, “Wavelet domain multidictionary learning for single image super resolution,” Journal of Electrical and Computer Engineering,vol.2015,Article ID 526508.
[2] H. Demirel and G. Anbarjafari, “Image Resolution Enhancement by Using Discrete and Stationary Wavelet Decomposition”, IEEE Trans. Image Processing, Vol. 20, No. 5, pp. 1458-1460,May. 2011.
[3] Sarwar, ArifandKhattak, “Super-Resolution using combination of wavelet transform and interpolation based method,” World comp proceedings, 2013
[4] Kim,Min,Wongeun oh and Lee “Medical Image Enhancement Algorithm Using EdgeBasedDenoising and Adaptive Histogram Stretching,” vol.5,pp. 25-38,2013
[5] Agrawal and Dash, “Image Resolution Enhancementusing Lifting Waveletand Stationary Wavelet Transform,” International Conference on Electronic Systems, Signal Processing and Computing Technologies ,2014
[6] Dipalee Gupta1, Siddhartha Choubey,” Discrete Wavelet Transform for Image Processing”, International Journal of Emerging Technology and Advanced Engineering,vol.4,Issue 3,March2015
Keywords
Discrete wavelet transform (DWT),Edge detection, Haar wavelet transform