1169 
AN IMPROVED IHS FUSION METHOD FOR MERGING MULTI-SPECTRAL AND 
PANCHROMATIC IMAGES CONSIDERING SENSOR SPECTRAL RESPONSE 
Jia Xu, Zequn Guan, Jie Liu 
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, China 
-jiaxu_whu@yahoo.com.cn 
KEY WORDS: image processing, sharpening, image fusion, intensity-hue-saturation (IHS) transform, spectral response 
ABSTRACT: 
While many remote sensing and GIS applications require both the spatial resolution and spectral resolution be high, image fusion, or 
in other words, image sharpening, is a useful technique. To date, numerous image fusion techniques have been developed. However, 
some undesirable effects such as modified spectral signatures and resolution overinjection are produced. In this paper, a novel 
spectral preservation fusion method for remotely sensed images is presented by considering the physical characteristics of sensors. It 
is mainly based on the fast intensity-hue-saturation (IHS) transform but improved in two parts: the construction of intensity 
component and the injection method of detail information. In the proposed method, the spectral sensitivity of the multispectral and 
panchromatic sensors has been taken into account and all the multispectral bands can be fused at the same time. Experiments carried 
out on IKONOS, Landsat 7 ETM+ and EO-1 ALI images show that the proposed method can preserve spatial details and minimize 
spectral distortion. 
1. INTRODUCTION 
Most of the newest remote sensing systems, such as Landsat 7, 
SPOT, IKONOS, QuickBird, EO-1, ALOS provide sensors with 
one high spatial resolution panchromatic (PAN) and several 
multispectral (MS) bands simultaneously. Meanwhile, an 
increasing number of applications, such as feature detection, 
change monitoring, and land cover classification, often demand 
the use of images with both high spatial and high spectral 
resolution. As a result, the fusion of HRP and LRM images has 
become a powerful solution and many image fusion methods 
have been proposed over the last two decades (Pohl et al, 1998; 
Lau et al, 2000; Wang et al,2005). However, as the physical 
spectral characteristic of the sensors are not considered during 
the fusion process, some undesirable effects such as modified 
spectral signatures and resolution overinjection are produced. 
Recently, Otazu et al (2005) has presented a technique which 
takes into account the physical electromagnetic spectrum 
response of sensors during the fusion process and successfully 
applied it to wavelet-based image fusion methods7. Some 
image fusion methods which employ the information of sensor 
spectral response have already been carried out on IKONOS 
images and demonstrated to be effective (Gonzalez-Audicana et 
al,2006; Dou et al, 2007; Zhang et al,2007). 
In this paper, after analyzing and comparing the radiometric 
properties of different sensors, we present a new improved 
method based on the fast IHS transform which takes the sensor 
spectral response into account. The proposed method minimizes 
spectral distortion and is capable of merging all the MS bands at 
the same time. To evaluate the performance and efficiency of 
the proposed method, experiments are carried out on IKONOS, 
Landsat 7 ETM+ and EO-1 ALI images. The proposed method 
is compared together with traditional IHS method and three 
typical modified IHS methods both visually and quantitatively. 
2. SPECTRAL CHARACTERISTICS OF SENSORS 
Problems and limitations associated with the available fusion 
techniques have been reported by many studies (Zhang,2000). 
The most significant problem may be the spectral distortion of 
fused images. To understand the influence of senor spectral 
response on panchromatic and multispectral image fusion, the 
spectral characteristics of different sensors are investigated in 
detail. 
Satellite 
(Sensor) 
Spectral range 
(pm) 
Corresponding MS 
Bands 
Landsat 7 
0.52-0.90 
2(G), 3(R), 4(NIR) 
IKONOS 
0.45-0.90 
1(B), 2(G), 3(R), 
4(NIR) 
Quickbird 
0.45-0.90 
1(B), 2(G), 3(R), 
4(NIR) 
SPOT 5 
0.48-0.71 
1(G), 2(R) 
IRS P6 
0.50-0.85 
1(G), 2(R), 3(NIR) 
EOl (ALI) 
0.48-0.69 
2(B), 3(G), 4(R) 
ALOS 
0.52-0.77 
2(G), 3(R) 
Table 1. Spectral ranges of PAN sensors 
2.1 Spectral range of panchromatic sensor 
A major reason for the significant spectral distortion in image 
fusion is the wavelength extension of the new satellite PAN 
sensors. Table 1 shows the spectral ranges of different PAN 
sensors. It is obvious that their spectral ranges are different. The 
spectral ranges of IKONOS, QuickBird and Landsat 7 are wider 
than the others and extended from the visible into the near 
infrared, which are different from that of SPOT, IRS, ALI and 
ALOS. This difference makes the grey value relationship of an 
IKONOS, Quickbird or Landsat 7 panchromatic image 
significant different from that of other panchromatic images. 
For example, as the high reflectivity in near infrared band,