|
Tropical Journal of Pharmaceutical Research
Pharmacotherapy Group, Faculty of Pharmacy, University of Benin, Benin City, Nigeria
ISSN: 1596-5996 EISSN: 1596-5996
Vol. 15, No. 9, 2016, pp. 1983-1993
|
Bioline Code: pr16262
Full paper language: English
Document type: Research Article
Document available free of charge
|
|
Tropical Journal of Pharmaceutical Research, Vol. 15, No. 9, 2016, pp. 1983-1993
en |
Efficient representation of texture details in medical images by fusion of Ripplet and DDCT transformed images
Dogra, Ayush; Agrawal, Sunil & Goyal, Bhawna
Abstract
Purpose: To evaluate and compare the performance of Ripplet Type-1 transform and directional
discrete cosine transform (DDCT) and their combinations for improved representation of MRI images
while preserving its fine features such as edges along the smooth curves and textures.
Methods: In a novel image representation method based on fusion of Ripplet type-1 and
conventional/directional DCT transforms, source images were enhanced in terms of visual quality using
Ripplet and DDCT and their various combinations. The enhancement achieved was quantified on the
basis of peak signal to noise ratio (PSNR), mean square error (MSE), structural content (SC), average
difference (AD), maximum difference (MD), normalized cross correlation (NCC), and normalized
absolute error (NAE). To determine the attributes of both transforms, these transforms were combined
to represent the entire image as well. All the possible combinations were tested to present a complete
study of combinations of the transforms and the contrasts were evaluated amongst all the combinations.
Results: While using the direct combining method (DDCT) first and then the Ripplet method, a PSNR
value of 32.3512 was obtained which is comparatively higher than the PSNR values of the other
combinations. This novel designed technique gives PSNR value approximately equal to the PSNR’s of
parent techniques. Along with this, it was able to preserve edge information, texture information and
various other directional image features. The fusion of DDCT followed by the Ripplet reproduced the
best images.
Conclusion: The transformation of images using Ripplet followed by DDCT ensures a more efficient
method for the representation of images with preservation of its fine details like edges and textures.
Keywords
Ripplet; Directional discrete cosine transform (DDCT); Peak signal to noise ratio; MSE (mean square error); SC (structural content); MD (maximum difference); NCC (normalized cross correlation
|
|
© Copyright 2016 - Tropical Journal of Pharmaceutical Research Alternative site location: http://www.tjpr.org
|
|