The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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In this paper, the efficiency of three different merging 
techniques (Principal Component, IHS, and Brovey Transform) 
is examined, in order to improve the spatial resolution of very 
high resolution aerial photographs (1:35.000 scale panchromatic) 
with the Landsat 7 ETM imagery. The aim was to get best 
enhanced merged aerial imagery for the visual interpretation. 
Principal Component method, which is the first method used in 
the study, calculates principal components, remaps the high 
resolution image into the data range of first principal 
component and substitutes it for first principal component, then 
applies an inverse principal components transformation. The 
Principal Component method is best used in applications that 
require the original scene radiometry (color balance) of the 
input multispectral image to be maintained as closely as 
possible in the output file. As this method scales the high 
resolution data set to the same data range as Principal 
Component 1, before the Inverse Principal Component 
calculation is applied, the band histograms of the output file 
closely resemble those of the input multispectral image. 
Unfortunately, this radiometric accuracy comes at the price of a 
large computational overhead. The Principal component method 
is consequently the slowest of the three methods offered and 
requires the most system resources. Another result of this 
methodology is that the output file tends to have the same data 
range as the input multispectral file (Erdas Field Guide,2006). 
Second merging method (IHS) works by assessing the spectral 
overlap between each multispectral band and the high 
resolution panchromatic band and weighting the merge based 
on these relative wavelengths. Therefore, it works best when 
merging images (and bands) where there is significant overlap 
of the wavelengths. As such, it may not produce good results 
when merging SAR imagery with optical imagery, for example. 
Normally, the biggest limitation of a method based on IHS 
processing is that it can only process three bands at a time 
(because of using the RGB to IHS method). However, the color 
consistency is so good that this implementation of the approach 
enables images with more than three bands to be merged by 
running multiple passes of the algorithm and merging the 
resulting layers. The technique can be used to merge different 
sensors (such as merging SPOT 4 data with Landsat5) (Erdas 
Field Guide,2006). 
Lastly used merging method (Brovey Transform) uses a ratio 
algorithm to combine the images. The Brovey Transform was 
developed to visually increase contrast in the low and high ends 
of an images histogram (i.e. to provide contrast in shadows, 
water and high reflectance areas such as urban features). 
Consequently, the Brovey Transform should not be used if 
preserving the original scene radiometry is important. However, 
it is good for producing RGB images with a higher degree of 
contrast in the low and high ends of the image histogram and 
for producing visually appealing images 8 Erdas Field 
Guide,2006). 
Since the very high difference at the resolution of source data, 
the techniques give very different results. The general 
conclusion is that if the original source imagery is used, 
Principal Component, and Brovey Transform merging 
techniques is preferable for such kind of imagery. 
In addition to previous ones, some other methods were also 
tested to enhance the merge imagery. In another method, firstly 
the multispectral Landsat 7 ETM imagery was merged with 
Landsat 7 ETM panchromatic imagery and finaly this imagery 
was merged with aerial photographs again with three different 
merging techniques. The results showed that this method 
creates better merged imagery. 
In the other method, at the first step multispectral Landsat 7 
ETM imagery was resample to higher resolution imageries (20, 
10, 5 meters resolutions) step by step. At the second step, these 
three images were enhanced with filtering. Finally, 
panchromatic aerial imagery was merged with these this 
resampled Landsat imagery again with three different merging 
techniques. 
In all approaches, Brovey Transform and Principal Component 
techniques serve well the purpose of increasing resolution of the 
low resolution images with the high resolution images. 
However, all methods should be tested in different areas by 
using multispectral and panchromatic images which were taken 
in different time frames to define the overall performances of 
these methods and merging techniques. 
1.2 Study Area and Data 
The study area is situated in the west of Izmir, which is the third 
biggest city of Turkey. The area shows the characteristic of 
much of the Aegean region, with agriculture and urban lands 
dominating valley bottoms and deciduous forests covering 
steeper areas. The area is generally rural. In the East of the 
study area there is a small village having some small farmlands. 
Izmir- £e§me motorway and national road extend from west to 
northeast of the study area. 
Figure 1. Study area and data (a: Aerial photographs, b: Landsat 
panchromatic, c: Landsat multispectral) 
Image data for the study are eight 1:35.000 scale black and 
white aerial photographs and Landsat-7 ETM imagery. Aerial