Optimization of Image Fusion using Genetic Algorithms and Discrete Wavelet Transform

Image fusion is the process of combining the most relevant information from multiple source images to obtain an accurate fused image. In this paper, we want to fuse visual and thermal satellite images. In order to provide enhanced information, we have investigated techniques of image fusion to obtain the most accurate information. This paper presents a technique which will produce an accurate fused image using discrete wavelet transform (DWT) for feature extraction and using Genetic Algorithms (GAs) to get the more optimized combined image. The performance of the proposed image fusion scheme is evaluated with mutual information (MI), root mean square error (RMSE), and it is also compared to the fused image that is generated by using Pixel Level GA based Image Fusion (PLGA_IF) and Discrete Wavelet Transform based Image Fusion (DWT_IF) techniques. Simulation results conducted with DWT and GA show that the proposed method outperforms the existing image fusion algorithms.