The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
1255 
c) Traditional IHS Result d) Improved IHS Result 
Figure 3: Image Fusion Result 
a) Original MS 4m 
b) Degraded MS 16m 
VALIDATION AND DISCUSSION 
3.1 Visual Comparison 
Comparing Fig.3(d) and Fig.3(c) with Fig.3(a), it is found that 
result retrieved from traditional method is a little too blue and 
grey, while the proposed method is closer to the reference 
image in tone. 
UIQI is a comprehensive image quality index (Wang, Z., et 
al. ,2002), which has been used to measure the similarity 
between two images. UIQI is defined as (10) and the result is 
shown in Table 3. 
Vjm 2g-,4 o-g 
WA<r B 
Band 
Origin 
IHS 
Proposed Method 
1 
10.1021 
13.1679 
14.9425 
2 
17.6524 
14.5899 
16.3799 
3 
23.0011 
15.8605 
17.6275 
4 
30.8366 
17.1412 
18.8309 
Table 1: Average Gradient of Reference and the Two Fused 
Images 
Band 
IHS 
Proposed Method 
1 
0.024133 
0.024763 
2 
0.0256 
0.024226 
3 
0.03775 
0.034866 
4 
0.042655 
0.039324 
Table 2: Relative Difference between Reference and the Two 
Fused Images 
3.2 Quantitative Assessment 
Three image indexes is used to assess the fusion result 
compared to original MS image. Average gradient (AG) assess 
sharpness of image, which is calculated by (8) and the 
assessment is shown in Table 1. 
m ff jl i' flsfra&h 
1 y yd* *■» ' » 
where M, N is column and row number of the image Z. 
Relative difference (RD) is an index to assess the distortion of 
fused image compared with reference image. RD is calculated 
by (9) and the result is shown in Table 2. 
Band 
IHS 
Proposed Method 
1 
0.827015 
0.84231 
2 
0.92246 
0.93537 
3 
0.936051 
0.947459 
4 
0.91383 
0.926604 
Table 3: UIQI between Reference and the Two Fused Images 
Table 1 shows that the fusion result retrieved from the proposed 
method is sharper than traditional method in every band and is 
closer to the reference image except band 1. Such result is 
expected because the improved histogram matching method 
extract more spatial detail. Table 2 shows that the proposed 
method lead to less RD than traditional method in every band, 
which means less spectral distortion is introduced by employing 
the improved histogram matching method. Table 3 shows that 
the proposed method produces fusion image with higher UIQI 
than traditional IHS method, which is caused by higher 
sharpness and lower spectral distortion. 
t r* v 1 
where A and F are reference image and fused image 
respectively. 
4. CONCLUSION 
The paper proposed an improved IHS image fusion method by 
proposing a new histogram matching method. Histogram 
matching process is analyzed and improved by introducing an 
image vector space. The fusion result of the proposed method is 
satisfactory. As histogram matching is a necessary step for most 
image fusion methods, the proposed histogram matching 
method could be applied to improve those methods.