Image Fusion Based On Dtcwt & Pca In Presence Of Noise

Abstract: image fusion is a process of combining relevant information from two or more images into a more informative single image. Image fusion technique improves the quality of the image. In this paper, the fusion is done using dual tree complex wavelet transform and principal component analysis. The images affected by noise are taken as the set of input images. The results show the proposed algorithm has better visual quality. The fusion technique is very much useful in diagnosing and treating cancer in medical fields. This paper is based on fusion of input noisy images using Dual Tree Complex Wavelet Transform and applying Principal Component Analysis (PCA) for fused image such that better image quality is obtained and estimated using various Image quality Metrics. The noise is removed from image and better PSNR values are also obtained.

Keywords: Image fusion, Dual tree complex wavelet transform, Principal component analysis, Image quality metrics