Image Zooming Using Inverse Slantlet Transform

Authors

  • Ahlam Hanoon Department of Computer Engineering/ Collage of Engineering/ University of Baghdad

Abstract

Digital image is widely used in computer applications. This paper introduces a proposed method of image zooming based upon inverse slantlet transform and image scaling. Slantlet transform (SLT) is based on the principle of designing different filters for different scales.

      First we apply SLT on color image, the idea of transform color image into slant, where large coefficients are mainly the   signal and smaller one represent the noise. By suitably modifying these coefficients , using scaling up image by  box and Bartlett filters so that the image scales up to 2X2 and then inverse slantlet transform from modifying coefficients using to the reconstructed image .

      From the simulation result, it has been found that the reconstructed image is 2X2 larger than the image that found from the inverse without scaling up the coefficients.

      Comparison of image zooming using inverses SLT by box and Bartlett filters, found that, because of the linear interpolation done by using Bartlett the image appears to be smoother than the image obtained using a box filter.

      The performance of these techniques (image zooming using inverse SLT) has been evaluated by computer programs with MATLAB 7.04 (R2007a) language.

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References

[1] G Panad, P.K. Dash, A.K. Pradhan and S.K. Mehar, "Data Compression of Power Quality Events Using the Slantlet Transform ". IEEE. Transaction on power Delivery, vol.17.2, April 2002.
[2] I.W Selesenick. "Discrete Wavelet Transform of Aaproximation Order 2 With Improved Time Localization-The Slantlet Transform" Polytechic University–Electrical Engineering. GMetrotech Centre Brooklyn, NY 11201-3840, 1998.
[3] I.W Selesnick, "The Slantlet Transform", IEEE.Tranction on Signal Processing, Vol.47, No. 5, MAY 1999.
[4] Peter Chien and Emily Kwok. Psych 221/ EE 362 project: Image Scaling. Prof.Brian Wandell Winter 1999.
[5] Mohammed Hazim Abdul – Kareem "Optimum Technique for Data File Denoising". M.Sc. Thesis University of Baghdad, Collage of Engineering, Electrical Eng. Dept. June 2007.
[6] Abbas Hussien Miry "Image Compression Using Slantlet Transform", M.Sc. Thesis University of Baghdad, Collage of Engineering, Electrical Eng. Dept. June 2007.

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Published

2009-06-01

How to Cite

Image Zooming Using Inverse Slantlet Transform. (2009). Al-Khwarizmi Engineering Journal, 5(2), 54-65. https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/559

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