A Novel Noisy Image Fusion Technique Using Dual-Tree Complex Wavelet Transform.

摘要

Nowadays Image fusion is become very popular for its application in various real life applications such as remote sensing applications, medical image diagnosis. The non-idle nature of practical imaging systems the capture images are corrupted by noise, hence Fusion of images is an integrated approach where the reduction of noise is essential. Discrete Wavelet Transform (DWT) has a wide range of application in fusion of noise images. However shift-invariance is important in ensuring robust subband fusion. To overcome this, Dual-tree Complex Wavelet Transform (DT-CWT) is introduced for fusion of noise images. Complex wavelet transform is complex valued extension of the standard wavelet. Experiments are carried out on a number of images like SAR images, MRI images, doll images and toy images to evaluate performance of the proposed method. Results shows that the DT-CWT method is better than that of DWT method in terms of quality measures peak signal-to-noise ratio, cross correlation and image visual quality.