Enhanced Image Fusion Algorithm using Laplacian Pyramid and Spatial Frequency Based Wavelet Algorithm
N. Indhumadhi1, G. Padmavathi2
1N. Indhumadhi, M. Phil Research Scholar, Avinashilingam Deemed University for Women, Coimbatore, India.
2Dr. G. Padmavathi, Professor and Head, Department of Computer Science, Avinashilingam Deemed University for Women, Coimbatore, India.
Manuscript received on October 09, 2011. | Revised Manuscript received on October 24, 2011. | Manuscript published on November 05, 2011. | PP: 298-303 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0232101511/2011©BEIESP
Abstract: The aim of image fusion is to combine relevant information from two or more source images into one single image such that the single image contains most of the information from all the source images. The successful fusion of images acquired from different modalities or instruments is of great importance in many applications, such as medical imaging, microscopic imaging, remote sensing, computer vision and robotics. The algorithm begins by applying 2D-DWT to decompose the input images. The lower approximations are subjected to pixel-based Laplacian fusion algorithm. The SF algorithm combined with wavelet fusion algorithm is used for higher approximations. The new sets of detailed and approximate coefficients from each image are then added to get the new fused coefficients. The final step then performs inverse DWT with the new coefficients to construct the fused image. Experimental results demonstrate the proposed fusion algorithm can obtain the quality output image, both in visual effect and objective evaluation criteria. Four performance metrics, namely, Root Mean Square Error (RMSE), Peak Signal to Noise Ratio (PSNR) and speed of fusing images, were used during experimentation. All the experiments showed that the proposed hybrid model is an improved version to fuse images when compared with pixel-based and wavelet-based algorithms.
Keywords: 2D-DWT, pixel-based Laplacian fusion algorithm, SF, CWD.
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