A simple and efficient image fusion algorithm based on standard deviation in wavelet domain

2016 ◽  
Author(s):  
Nirmala Paramanandham ◽  
Kishore Rajendiran
Keyword(s):  
Standard Deviation ◽  
Image Fusion ◽  
Wavelet Domain ◽  
Fusion Algorithm

Multi-Focus Image Fusion Based on Pyramid Decomposition

2014 ◽  
Vol 672-674 ◽  
pp. 1954-1957
Author(s):  
Yu Bing Dong ◽  
Ming Jing Li ◽  
Guang Liang Cheng
Keyword(s):  
Standard Deviation ◽  
Image Fusion ◽  
Objective Evaluation ◽  
Decomposition Algorithm ◽  
Fusion Process ◽  
Evaluation Index ◽  
Laplacian Pyramid ◽  
Matlab Simulation ◽  
Fusion Algorithm ◽  
Focus Image

Image fusion algorithm is very important in image fusion process. Image fusion algorithm based on pyramid decomposition was reviewed in this paper. Pyramid decomposition algorithm mainly includes Contrast pyramid, Gradient Pyramid, Laplacian Pyramid and Ratio Pyramid. The fusion algorithms based on pyramid decomposition were respectively applied in multi-focus images, advantage and disadvantage were summarized and application was given. Fusion results were given by MATLAB simulation. Objective evaluation index including of mean, standard deviation, entropy and average gradient was calculated in this paper. Image fusion algorithm should be selected according to the information extracted and the aim of fusion.

scholarly journals Image fusion algorithm based on block-DCT in wavelet domain

2011 ◽  
Vol 60 (11) ◽  
pp. 114205
Author(s):  
Gan Tian ◽  
Feng Shao-Tong ◽  
Nie Shou-Ping ◽  
Zhu Zhu-Qing
Keyword(s):  
Image Fusion ◽  
Wavelet Domain ◽  
Fusion Algorithm ◽  
Block Dct

IMAGE FUSION METHOD BASED ON SHORT SUPPORT SYMMETRIC NON-SEPARABLE WAVELET

2004 ◽  
Vol 02 (01) ◽  
pp. 87-98 ◽  
Author(s):  
LIU BIN ◽  
JIAXIONG PENG
Keyword(s):  
Standard Deviation ◽  
Image Fusion ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Activity Measurement ◽  
Fusion Method ◽  
Fusion Algorithm ◽  
Dilation Matrix ◽  
Image Fusion Method

In this paper, image fusion method based on a new class of wavelet — non-separable wavelet with compactly supported, linear phase, orthogonal and dilation matrix [Formula: see text] is presented. We first construct a non-separable wavelet filter bank. Using these filters, the images involved are decomposed into wavelet pyramids. Then the following fusion algorithm was proposed: for low-frequency part, the average value is selected for new pixel value, For the three high-frequency parts of each level, the standard deviation of each image patch over 3×3 window in the high-frequency sub-images is computed as activity measurement. If the standard deviation of the area 3×3 window is bigger than the standard deviation of the corresponding 3×3 window in the other high-frequency sub-image. The center pixel values of the area window that the weighted area energy is bigger are selected. Otherwise the weighted value of the pixel is computed. Then a new fused image is reconstructed. The performance of the method is evaluated using the entropy, cross-entropy, fusion symmetry, root mean square error and peak-to-peak signal-to-noise ratio. The experiment results show that the non-separable wavelet fusion method proposed in this paper is very close to the performance of the Haar separable wavelet fusion method.

Image Fusion Algorithm Based on Gradient Pyramid and its Performance Evaluation

2014 ◽  
Vol 525 ◽  
pp. 715-718 ◽  
Author(s):  
Ming Jing Li ◽  
Yu Bing Dong ◽  
Xiao Li Wang
Keyword(s):  
Performance Evaluation ◽  
Standard Deviation ◽  
Image Fusion ◽  
Color Image ◽  
Decomposition Algorithms ◽  
Original Image ◽  
Fusion Algorithm ◽  
Multi Scale ◽  
Focus Image ◽  
Simulation Results

Image fusion algorithm based on gradient pyramid is one of the multi-scale, multi-resolution decomposition algorithms. Original image was decomposed into Gauss pyramid, after that, gradient decomposition was completed on each layer in four directions, and fusion effect was evaluated by taking using of entropy, average gradient, mean and standard deviation. Simulation results show that gradient pyramid algorithm is effective to multi-focus image and color image.

Metal Stamping Character Image Fusion Algorithm Based on Multi-directional Illumination

2018 ◽  
Vol 30 (9) ◽  
pp. 1637
Author(s):  
Zhong Xiang ◽  
Jianfeng Zhang ◽  
Miao Qian ◽  
Zhenyu Wu ◽  
Xudong Hu
Keyword(s):  
Image Fusion ◽  
Fusion Algorithm ◽  
Metal Stamping
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