Image fusion using intuitionistic fuzzy sets |
| |
Affiliation: | 1. School of Software, Yunnan University, Kunming 650091, China;2. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;3. School of Information Technology, Deakin University, Geelong, VIC 3216, Australia;4. School of Information, Yunnan University, Kunming 650091, China |
| |
Abstract: | Image fusion is the process of combining one or more images which are obtained from different environment into a single image which is more useful for further image processing tasks. Image registration and image fusion are of great importance in defence and civilian sectors, particularly for recognizing a ground/air force vehicle and medical imaging. In this paper a new way is drawn to fuse two or more images by using maximum, minimum operations in intuitionistic fuzzy sets (IFSs). IFSs are more suitable for image processing since every digital image have lot of uncertainties. In processing phase, images are reformed into intuitionistic fuzzy images (IFIs). Entropy is employed to obtain the optimum value of the parameter in membership and non-membership function. Then the resulting IFIs are disintegrated into image blocks and the corresponding blocks of the images are reunioned by finding the count of blackness and whiteness of the blocks. This paper evaluates the performance of simple averaging (AVG), principal component analysis (PCA), discrete wavelet transform (DWT), stationary wavelet transform (SWT), dual tree complex wavelet transform (DTCWT), multi-resolution singular value decomposition (MSVD), nonsubsampled contourlet transform (NSCT) and IFS (proposed method) in terms of various performance measure. The experimental and comparison results show that luminance and contrast is of great importance for image processing and prove that the proposed method is better than all other methods. |
| |
Keywords: | Intuitionistic fuzzy set Intuitionistic fuzzy image Entropy Image fusion |
本文献已被 ScienceDirect 等数据库收录! |
|