Polarimetric and Multi-spectral Image Fusion Based on HSI Color System and Wavelet Transform

2010 ◽  
Vol 39 (s1) ◽  
pp. 43-47 ◽  
Author(s):  
陈振跃 CHEN Zhen-yue ◽  
王霞 WANG Xia ◽  
邹晓风 ZOU Xiao-feng
2013 ◽  
Vol 427-429 ◽  
pp. 1641-1644
Author(s):  
Liu Ming ◽  
Shu Hui Li

A new improved image fusion algorithm is proposed for multi-spectral image (MUL) and the high-resolution panchromatic image (PAN) based on intensity-hue-saturation (IHS) transform combined with wavelet transformation (WT). Firstly, the multi-spectral image is transformed into the IHS space for getting the intensity component (I).Then the high-resolution panchromatic image and I were matched with histogram. Secondly, the PAN and I were decomposed respectively by WT and fused to obtain the new I by the inverse WT. Finally, the fusion image was obtained by inverse IHS transform. four evaluate indicators are defined in this paper. By experiment research, the results show that this new method can effectively improve the fusion effect.


2014 ◽  
Vol 14 (2) ◽  
pp. 102-108 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Junfeng Gao ◽  
Zhongsheng Qian

Abstract In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.


2014 ◽  
Author(s):  
Yoonsuk Choi ◽  
Ershad Sharifahmadian ◽  
Shahram Latifi
Keyword(s):  

2011 ◽  
Vol 1 (3) ◽  
Author(s):  
T. Sumathi ◽  
M. Hemalatha

AbstractImage fusion is the method of combining relevant information from two or more images into a single image resulting in an image that is more informative than the initial inputs. Methods for fusion include discrete wavelet transform, Laplacian pyramid based transform, curvelet based transform etc. These methods demonstrate the best performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. In particular, wavelet transform has good time-frequency characteristics. However, this characteristic cannot be extended easily to two or more dimensions with separable wavelet experiencing limited directivity when spanning a one-dimensional wavelet. This paper introduces the second generation curvelet transform and uses it to fuse images together. This method is compared against the others previously described to show that useful information can be extracted from source and fused images resulting in the production of fused images which offer clear, detailed information.


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