Consistent pan-sharpening based on multistage joint and dual bilateral filters

In this paper, we propose a new pan-sharpening method with better noise rejection capabilities. It is based on consistent combination of large and small scale features obtained from the decomposition of high spectral resolution multi-spectral (MS) and high spatial resolution panchromatic (PAN) images. In the decomposition process, MS and PAN images are used to extract the features with the help of joint and dual bilateral filters, respectively. These filters take care of the relationship between MS and PAN images and decompose them into a base layer (large-scale) and a detail layer (small-scale). Since the joint bilateral filter (JBF) preserves the edges of the auxiliary image, it is used for decomposition of MS images where the different layers are computed by using the PAN image as an auxiliary image. In a similar manner, the different layers of the PAN image are obtained by using dual bilateral filter (DBF) which preserves the edges of both (MS and PAN) input images. This process is extended to multistage decomposition to obtain a bilateral image pyramid. The base and detail layers of both MS and PAN images obtained at various stages are combined using a weighted sum, respectively. Finally, the computed weighted sum of detail layer (small-scale) of the PAN image is fused separately to the weighted base layers (large-scale) of the MS images. The proposed method is tested over the images obtained from Quickbird and Worldview-2 satellite sensors. The experimental results are compared with the widely popular methods and recently proposed bilateral filter based methods. The experimental results demonstrate that the proposed method performs better for all satellite sensors.