COMPARISON OF DIFFERENT FUSION ALGORITHMS IN URBAN AND AGRICULTURAL AREAS USING SAR (PALSAR AND RADARSAT) AND OPTICAL (SPOT) IMAGES

Image fusion techniques of remote sensing data are formal frameworks for merging and using images originating from different sources. This research investigates the quality assessment of Synthetic Aperture Radar (SAR) data fusion with optical imagery. Two different SAR data from different sensors namely RADARSAT-1 and PALSAR were fused with SPOT-2 data. Both SAR data have the same resolutionsand polarisations; however images were gathered in different frequencies as C band and L band respectively. This paper contributes to the comparative evaluation of fused data for understanding the performance of implemented image fusionalgorithms such as Ehlers, IHS (Intensity-Hue-Saturation), HPF (High Pass Frequency), two dimensional DWT (Discrete Wavelet Transformation), and PCA (Principal Component Analysis) techniques. Quality assessments of fused imageswere performed both qualitatively and quantitatively. 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 the fused images. The evaluations were performed by categorizing the test area into two as “urban” and “agricultural”. It has been observed that some of the methodshave enhanced either the spatial quality or preserved spectral quality of the original SPOT XS image to various degrees while some approaches have introduced distortions. In general we noted that Ehlers’ spectral quality is far better than those of the other methods. HPF performs almost best in agricultural areas for both SAR images

Comparison of different fusion algorithms in urban and agricultural areas using sar (palsar and radarsat) and optical (spot) images

Image fusion techniques of remote sensing data are formal frameworks for merging and using images originating from different sources. This research investigates the quality assessment of Synthetic Aperture Radar (SAR) data fusion with optical imagery. Two different SAR data from different sensors namely RADARSAT-1 and PALSAR were fused with SPOT-2 data. Both SAR data have the same resolutions and polarisations; however images were gathered in different frequencies as C band and L band respectively. This paper contributes to the comparative evaluation of fused data for understanding the performance of implemented image fusion algorithms such as Ehlers, IHS (Intensity-Hue-Saturation), HPF (High Pass Frequency), two dimensional DWT (Discrete Wavelet Transformation), and PCA (Principal Component Analysis) techniques. Quality assessments of fused images were performed both qualitatively and quantitatively. 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 the fused images. The evaluations were performed by categorizing the test area into two as "urban" and "agricultural". It has been observed that some of the methods have enhanced either the spatial quality or preserved spectral quality of the original SPOT XS image to various degrees while some approaches have introduced distortions. In general we noted that Ehlers' spectral quality is far better than those of the other methods. HPF performs almost best in agricultural areas for both SAR images

Information-theoretic assessment of fusion of multispectral and panchromatic images

In this work we investigate the use of Shannon's information theory for the goal of devising quality scores of image fusion results, that do not require reference originals. In particular, the mutual information between resampled original and fused MS bands is used to measure the spectral quality, while the mutual information between the Pan image and the fused bands yields a measure of spatial quality. The rationale is that the normalized mutual information calculated either between any couple of bands, or between each MS band and the Pan image, should be unchanged after fusion, Le., when passing from the coarse scale of the MS data to the fine scale of the Pan image. Experimental results carried out on QuickBird and Ikonos data demonstrate that the results provided by the proposed information-theoretic method are in trend with analysis performed on spatially degraded data by means of such parameters as Walds's ERGAS, Wang and Bovik's QI, and the novel Q4 score index based on quaternions theory and recently proposed by the authors. However, the novel method requires no reference and is therefore directly applicable in all practical cases