Fusion of sar images (palsar and radarsat-1) with multispectral spot image: A comparative analysis of resulting images

Land use information is one of the most useful input element in forming policies concerning to economic, environmental issues at national and also at global levels. With the view of these different spectral, temporal and spatial qualified sensors are developed. On the other hand for some applications single sensor imagery might not be enough to gather information from earth surface. Fusion of satellite images with different spatial and spectral resolutions plays an important role for extracting information. Image fusion is an application for making use of two or more complementary images/spectral bands of the same or different sensors for the same area to get more information and to enhance the quality of image interpretation. This research investigates the quality assessment of SAR data fusion with optical imagery. Two different SAR data from different sensors namely RADARSAT-1 and PALSAR were fused with SPOT-2 data. Although the PALSAR and the RADARSAT-1 images have the same resolutions and polarisations, images were gathered in different frequencies (L band and C band respectively). Particularly in this case the operating frequency is a key factor in the penetration depth to see the affects on extracting information from fused images. This application describes a comparative study of multisensor image fusion techniques in preserving spectral quality of the fused images. IHS (Intensity-Hue-Saturation), HPF (High Pass Frequency), two dimensional DWT (Discrete Wavelet Transformation), and PCA (Principal Component Analysis) techniques are implemented for image fusion. For the statistical analysis bias, correlation coefficient (CC), Difference in Variance (DIV), Standard Deviation Difference (SDD), Universal Image Quality Index (UIQI) methods were applied on fused images. Statistically results depict that DCW fusion technique gives better result for both Radarsat-SPOT and PALSAR-SPOT fused images.