A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Global Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multifocus image fusion using artificial neural networks
Pattern Recognition Letters
Evaluation of focus measures in multi-focus image fusion
Pattern Recognition Letters
Multi-focus image fusion using pulse coupled neural network
Pattern Recognition Letters
A hybrid real-parameter genetic algorithm for function optimization
Advanced Engineering Informatics
Focused image recovery from two defocused images recorded with different camera settings
IEEE Transactions on Image Processing
Fusing images with different focuses using support vector machines
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
The multifocus imaging technique in petrology
Computers & Geosciences
Journal of Visual Communication and Image Representation
Mutual spectral residual approach for multifocus image fusion
Digital Signal Processing
Hi-index | 12.06 |
In an image captured by a CCD/CMOS sensor with an optical lens, only the objects within the depth of field are sharply focused. One way to get an everywhere-in-focus image is to fuse the images of the same scene which are taken with different focal settings. In this paper, a novel optimal method for multi-focus image fusion using differential evolution algorithm is presented. The source images are first decomposed into blocks. Then, the sharper blocks are selected by employing a sharpness criterion function. The selected blocks are finally combined to construct the fused image. The motivation of the proposed method lies in the fact that an optimized block size could be more effective than a fixed block size. Experimental results show that the proposed method outperforms other traditional methods and genetic algorithm based method in terms of both quantitative and visual evaluations.