Integration of SAR features into multispectral images based on the nonsubsampled contourlet and IHS transform

As a new image multiscale geometric analysis tool, the nonsubsampled contourlet transform (NSCT) has many advantages such as multiscale, localization and multidirection, and can efficiently capture the geometric information of images. Therefore, when the NSCT is introduced to image fusion, the characteristics of original images can be taken better and more information for fusion can be obtained. In this paper, a novel fusion algorithm for fusion of the synthetic aperture radar (SAR) image and multispectral images using conjointly the intensity-hue-saturation (IHS) transform and NSCT is proposed. In the proposed method, atrous wavelet is adopted to extract the detail information in low frequency parts fusion, and a new salience measure named as local inner product is introduced to select the high frequency coefficients. A PALSAR HH image of ALOS satellite despeckled by the Lee-sigma filter and HJ-1 multispectral images are used to evaluate the performance and efficiency of the proposed method. The fused images of each method are evaluated by qualitative and quantitative comparison and analysis compared with some traditional fusion rules. The experimental results indicate that the proposed method has the merits of better preservation of image definition and less loss of spectral information.