The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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relative adimensional global error in synthesis (ERGAS-Erreur 
Relative Globale Adimensionnelle de Synthèse) (Wald, 2002). 
Fusion methods are used for gathering information from SAR 
and Optical data. A comparative analysis described using L 
band Jersl SAR and Landsat TM data. IHS, Wavelet, PCA and 
High pass filtering (HPF) techniques are applied and mean, 
standard deviation, coefficient correlation and entropy factors 
are computed to qualify the fused images (Rokhmatuloh et 
al,2003, Shi,2005). Pal et al. 2007 fused four bands 1RS-1C to 
ERS-2 using PCA technique for enhancement of gathering 
geological information. 
In our study the quality assessment analyses were evaluated for 
multi sensor data. An HH polarized L band PALSAR, an HH 
polarized C band RADARSAT-1 image and a three band 
SPOT-2 XS were used for image fusion. IHS, PCA, HPF, 
DCW techniques were used for the fusion of each of 
RADARSAT-SPOT and PALSAR-SPOT images. All fused 
images compared visually and statistically to SPOT XS. Bias, 
CC, DIV, SDD and UIQI statistical analysis derived from fused 
images. 
image were used as SAR data. A SPOT HRV-2 XS 
multispectral imagery having three spectral bands with a 20 m 
resolution were used as optical data. PALSAR (Phased Array 
type L-band Synthetic Aperture Radar) data of ALOS satellite 
(Advanced Land Observing Satellite) is a new SAR mission 
which has observation capability of high spatial resolution. In 
this study a fine single polarized (FBS) mode PALSAR imagery 
with pixel size 6.25 m x 6.25 m and a Fine Beam 1 mode of 
RADARSAT-1 image with pixel size 6.25 m x 6.25 m were 
used. 
RADARSAT1 
PALSAR 
SPOT-2 
Date 
28/05/2006 
10/06/2006 
14 /05/2006 
Sensor 
SAR Fine 1 
PALSAR/FBS 
HRV/HRG 
Pixel Spacing 
6.25 m. 
6.25 m. 
20m 
Orbit 
55139 
2010 
Flight direction 
Ascending 
Ascending 
Processing 
SGF 
LI.5 
Polarization 
H/H 
H/H 
Swath 
50 km 
80 km 
60 km 
Incidence angle 
37-40 
41.5 
L29.6 
2. STUDY AREA 
In this research, Menemen (Izmir) Plain on the west of Gediz 
Basin in the Aegean Region of Turkey was selected as a study 
area that covers about 400 square km. The Aegean Sea lies on 
the west of the study area, and Manisa Province lies on the 
North (Figure 1). The study area covers both residential and 
agricultural areas. The area has a micro relief however the slope 
in general is 1 %. Texture and slope are important soil 
characteristics for SAR backscattering. 3 
Figure 1. Memenen plain 
Table l.Data information 
Before the image fusion process SAR images were pre- 
processed by the commonly used speckle reducing filter 
techniques. For the filtering of SAR images different sized 
kernel windows were used with Gamma filtering and 3x3 one 
was chosen. 
In this study image fusion was conducted at the pixel level. In 
order to avoid the combination of unrelated data spatial 
registration accuracies should be at the sub pixel. Therefore in 
fusion applications geometric correction is very important for 
registration of the images. After reducing the speckle effects of 
SAR images, SAR images were registered to SPOT image by 
using image to image rectification method with a root mean 
square error of less than 1 pixel. Cadastral maps in 1/5000 scale 
and topographic maps in 1/25000 scale were used for the 
rectification of SPOT images. 
In this study 4 fusion methods have been examined namely 
Intensity, Hue and Saturation (IHS), Principle Component 
Analysis (PCA), Discrete Wavelet Transformation (DWT) and 
High Pass Filter (HPF). 
3.2 Pre-processing 
3.3 Image Fusion Methods 
3. MATERIALS AND METHODOLOGY 
3.1 Data 
Two different SAR data from different sensors namely 
RADARSAT-1 and PALSAR were both fused with SPOT-2 
dhta (Table 1). 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. An HH polarized L 
band PALSAR and an HH polarized C band RADARSAT-1 
IHS method separates the Intensity, Hue and Saturation 
components of a RGB image. Three bands of an MS image are 
converted from RGB colour to IHS colour. Spatial frequency 
related I component is replacing the high resolution image and 
back transformation IHS to RGB is required (Pohl and Van 
Genderen,1998). 
PCA converts a multivariate data set of inter-correlated 
variables into new uncorrelated linear combinations of the 
original values (Pohl and Van Genderen,1998, Teggi et al,2003). 
The difference between IHS and PCA is that while IHS is used 
for 3 bands, PCA method can be used for more than three bands.