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Tamilarasi, M.
- Region Based Image Fusion Using Modified Contourlet Transform
Authors
1 Department of ECE, Pondicherry Engineering College, Pillaichavady, Puducherry, IN
2 Dept. of ECE, Pondicherry Engineering College, Pillaichavady, Puducherry, IN
3 Pondicherry Engineering College, IN
Source
Digital Image Processing, Vol 3, No 14 (2011), Pagination: 888-892Abstract
Image fusion techniques are applied in various fields such as remote sensing, medical imaging, concealed weapon detection, etc. Combining two or more images of the same scene usually produces an output image which provides increased interpretation capabilities and reliable results. In image fusion, data with different specifications such as resolution, spectral and spatial coordinates are combined. Image fusion algorithm can be categorized into pixel and feature levels. Region based method is one way of achieving the feature- level fusion. Segmentation plays a vital role in this fusion process where the features of the source images are extracted first using Edge based segmentation Consequently, the Contourlet transform is applied on the different regions and the coefficients from different regions are merged separately. Finally, the fused image is obtained by performing inverse Contourlet transform. The Laplacian pyramid employed in Contourlet transform is not the perfect transform from the point of view of image fusion, since it involves down-sampling procedure which makes it shift variant. Therefore, in order to yield better performance metric in the proposed work, the Contourlet transform is modified by replacing the Laplacian pyramid by Contrast pyramid. Region based image fusion using modified Contourlet transform and the Contourlet transform are applied on various images to compare their performances. Simulation results indicate that Region Based Image Fusion using Modified Contourlet transform produces better results than Contourlet transform in terms of entropy, correlation coefficient, PSNR and average gradient.Keywords
Contrast Pyramid, Directional Filter Bank, Image Fusion, Modified Contourlet Transform, Segmentation.
- Modified Embedded Contourlet Transform Based Medical Image Compression Using Soft Computing Techniques
Authors
1 Department of Electronics and Communication Engg, Chettinad College of Engineering and Technology, Puliyur, IN
2 Info Institute of Engineering, Coimbatore, IN
Source
Digital Image Processing, Vol 1, No 2 (2009), Pagination: 78-82Abstract
The main objective of this paper is to compress a medical image using contourlet transform used in different modalities of medical imaging. Recent reports on natural image compression have shown superior performance of contourlet transform, a new extension to the wavelet transform in two dimensions using nonseparable and directional filter banks. As far as medical images are concerned the diagnosis part(ROI) is of much important compared to other regions. Therefore those portions are segmented from the whole image using neural network based fuzzy logic technique. Contourlet transform is then applied to ROI portion which performs Laplacian Pyramid(LP) and directional filter banks to the resultant because of irectionality and anisotropy. The region of less significance are compressed using Discrete Wavelet Transform and finally modified embedded zerotree wavelet algorithm is applied which uses six symbols instead of four symbols used in Shapiro’s EZW to the resultant image which shows better PSNR and high compression ratio and finally Huffman coding is applied to get the compressed image.