Efficient representation of texture details in medical images by fusion of Ripplet and DDCT transformed images

Ayush Dogra,Bhawna Goyal,Sunil Agrawal

doi:10.4314/tjpr.v15i9.24

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

Highlights

Better representation of image details is most important step for executing different image processing tasks like image fusion, image registration [1,2] and image enhancement [3,4,5,6]
In this paper we proposed a novel technique of combining RT and directional discrete cosine transform (DDCT) by direct combination and using multiplication and addition operator for better representation of magnetic resonance imaging (MRI) images
Resultant image at 50000 coefficient using Ripplet transform showed the best results (Table 1) and only this image was combined with DCT transforms at all modes

Summary

Introduction

Better representation of image details is most important step for executing different image processing tasks like image fusion, image registration [1,2] and image enhancement [3,4,5,6]. These image processing tasks serve various fields like medical imaging and pharmaceutical sciences. The enhancement in the visual quality of medical images like MRI, CT, SPECT, X-Ray image quality lessens the probability of false diagnosis. Imaging is a key in medical diagnosis of many diseases and particle size analysis in tableting and encapsulation of medicines. In particle size analysis image enhancement technique is used for making particle measurements like particle size, morphology, shape analysis and grayscale or color

Methods

Results

Conclusion