Implementation of image fusion algorithm using MATLAB (LAPLACIAN PYRAMID)

M. Pradeep
2013 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)  
Image denoising is the first and much necessary step to execute before examining an image. Problems with the data acquisitive process, Imperfectness of instruments, and interferingness natural phenomena are the main reasons to spoil an image. The goal of denoising is to take out the utmost noise from an image while keeping as much as possible the important data, signal features. In this paper we have examined and compared the results of the Modified Haar Denoising algorithm using Laplacian
more » ... sing Laplacian pyramid and Adaptive segmentation with the other existing denoising methods. The noise affected image is denoised by Modified Haar DWT method using Laplacian pyramid and Adaptive thresholding. The comparison of the denoisng methods are done by using performance parameter Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE) between the pilot and noise affected image and PSNR, RMSE between pilot and reconstructed (denoised) image. The results tells that PSNR of proposed algorithm is higher than the other existing denoising methods and RMSE of proposed algorithm is lesser than the other existing denoising methods. As a result the denoised image will be visually appealing after reconstruction. For removing the noise from the image MATLAB is used to implement the proposed method in this paper.
doi:10.1109/imac4s.2013.6526401 fatcat:ojhk7nvhjjcghbtxdegywpmtma