Based on the idea of iteration, a simple and effective method for multi-focus image fusion is proposed. Firstly, two images are processed by Gaussian convolution, and the blurred images are obtained. Then, the area decision of image blocks are obtained through the original image subtracting the blurred images at different blocks and different levels. According to the principle of consistency, the subjection of image blocks is obtained by the area decision of image blocks. The area partition map is obtained by the subjection map at different levels. Finally, the fused image is obtained through the method of coefficient weighting. The experimental results show that the image quality obtained by the proposed method is superior to the traditional fusion method.
Multi-resolution is the good characteristics of wavelet transform. In wavelet transform domain, high frequency subband
of image is sparse. Less high frequency coefficient can be sampled by compressed sensing technology. In this study, for
an image, a sparse representation in the wavelet transform domain is found. Image is reconstructed by the orthogonal
matching pursuit (OMP) , compressive sampling matching pursuit (CoSaMP), iteratively reweighted least square (IRLS)
and Suspace Pursuit (SP), respectively. Different wavelet basis and sampling rate which affect the quality of the
reconstruction are discussed. Experimental result shows that performance of IRLS is the best, OMP are easy
implementation and fast speed, and Coif3 has a better performance than the other wavelet basis.
In this paper, a method to enhance the fingerprint image by using Log-Gabor filters is proposed. Firstly, a filter for
extracting fingerprint image texture feature is designed. Then, the high frequency components of fingerprint image are
extracted by filtering. Finally, the fingerprint image details can be improved by enhancing high frequency components.
Experimental results show that the proposed algorithm can effectively improve the quality of fingerprint image and the
reliability of fingerprint identification.
A method for image fusion based on multi-orientation gradient mode and non-down-sampled B-spline Wavelet
Transform is proposed, by using block partition of the image fusion method of thinking. Multi-directional gradient filters
are designed by directional derivative. High-frequency image blocks are distilled by non-down-sampled B-spline wavelet
transform, and are filtered by multi-directional gradient filters. Compared with the total value of the gradient of
corresponding high-frequency image block is in order to pick out a clear image of the block .Finally, the final fusion
image can be achieved by reconstructing clear picture block and application of the consistency constraints. This method
doesn't need wavelet inverse transform to reconstruct image, reserve the original images to achieve high-precision
integration. Experiments show that the method for multi-focus image fusion has good results and good stability.