Publication Type:

Journal Article

Source:

World Academy of Science, Engineering and Technology, Issue 65, p.816-821 (2010)

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-78751639844&partnerID=40&md5=70974d6b9276e8b6dcf57df4031ea61e

Keywords:

Approximation theory, Computational costs, Crystal lattices, Discrete wavelet transforms, Filter banks, Fourier transforms, Gabor filter, Gabor filter banks, Gabor filters, Gabor wavelets, Hexagonal lattice, Hexagonal lattices, Image Enhancement, Image interpolations, Image processing, Image quality, Imaging systems, Interpolation, Mean squared error, Medical images, Medical imaging, Optimal approximation, PDE model, Peak signal-to-noise ratio, Quality image, Rectangular domain, Signal to noise ratio, Windowing techniques, X-ray image

Abstract:

For about two decades scientists have been developing techniques for enhancing the quality of medical images using Fourier transform, DWT (Discrete wavelet transform),PDE model etc., Gabor wavelet on hexagonal sampled grid of the images is proposed in this work. This method has optimal approximation theoretic performances, for a good quality image. The computational cost is considerably low when compared to similar processing in the rectangular domain. As X-ray images contain light scattered pixels, instead of unique sigma, the parameter sigma of 0.5 to 3 is found to satisfy most of the image interpolation requirements in terms of high Peak Signal-to-Noise Ratio (PSNR), lower Mean Squared Error (MSE) and better image quality by adopting windowing technique.

Notes:

cited By (since 1996)2

Cite this Research Publication

S. Veni and Narayanankutty, K. A., “Image enhancement of medical images using gabor filter bank on hexagonal sampled grids”, World Academy of Science, Engineering and Technology, no. 65, pp. 816-821, 2010.