Comparative Analysis of Image Fusion Methods

Integration of more than one image in order to obtain a more accurate image which has all objects in focus is known as Image Fusion (IF). The images having sharpness give improved results than that of the blurry images. In most of the cases, it is really not possible to have a whole type of focused image in just one shot of the camera, as some of the parts appear to be of blurred form resulting from deep variations of scenes because of the focus quality of camera lenses. Image fusion is a potential tool in removing the above limitations. As through this, the resultant image is produced which preserves both spatial and spectral resolution. Various IF techniques such as pixel level, multi-scale methods have been used for the enhancement of an image which has been discussed in this paper. The comparative analysis has been done on various image fusion techniques. This paper discusses mainly the advantages and disadvantages of spatial and frequency domain methods.

[1]  Chuc D. Man,et al.  Comparison of various image fusion methods for impervious surface classification from VNREDSat-1 , 2018, ArXiv.

[2]  Liangpei Zhang,et al.  Boosting the Accuracy of Multispectral Image Pansharpening by Learning a Deep Residual Network , 2017, IEEE Geoscience and Remote Sensing Letters.

[3]  Joan Duran,et al.  A Variational Formulation for Hyperspectral and Multispectral Image Fusion , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

[4]  Vps Naidu Discrete Cosine Transform based Image Fusion Techniques , 2012 .

[5]  Ravindra Dhuli,et al.  Two-scale image fusion of visible and infrared images using saliency detection , 2016 .

[6]  Ashish Khare,et al.  Multiscale Medical Image Fusion in Wavelet Domain , 2013, TheScientificWorldJournal.

[7]  Shutao Li,et al.  Pixel-level image fusion: A survey of the state of the art , 2017, Inf. Fusion.

[8]  Yu Liu,et al.  Multi-focus image fusion with a deep convolutional neural network , 2017, Inf. Fusion.

[9]  Jie Xu,et al.  Compressed multi-scale feature fusion network for single image super-resolution , 2018, Signal Process..

[10]  H. D. Supreetha Gowda,et al.  Multimodal Biometric Recognition System Based on Nonparametric Classifiers , 2018, Data Analytics and Learning.

[11]  B. S. Manjunath,et al.  Multisensor Image Fusion Using the Wavelet Transform , 1995, CVGIP Graph. Model. Image Process..

[12]  Ying Liu,et al.  Multi-focus image fusion using deep support value convolutional neural network , 2019, Optik.

[13]  Jeff R. Harris,et al.  IHS transform for the integration of radar imagery with other remotely sensed data , 1990 .

[14]  Xiaohua Qiu,et al.  Guided filter-based multi-focus image fusion through focus region detection , 2019, Signal Process. Image Commun..

[15]  Le Song,et al.  A Novel Automatic Weighted Image Fusion Algorithm , 2009, 2009 International Workshop on Intelligent Systems and Applications.

[16]  Johannes R. Sveinsson,et al.  Multispectral and Hyperspectral Image Fusion Using a 3-D-Convolutional Neural Network , 2017, IEEE Geoscience and Remote Sensing Letters.

[17]  Ali Aghagolzadeh,et al.  Ensemble of CNN for multi-focus image fusion , 2019, Inf. Fusion.

[18]  Jie Liu,et al.  Multi-focus image fusion based on robust principal component analysis and pulse-coupled neural network , 2014 .

[19]  Yu Liu,et al.  Simultaneous image fusion and denoising with adaptive sparse representation , 2015, IET Image Process..

[20]  Lindsay I. Smith,et al.  A tutorial on Principal Components Analysis , 2002 .

[21]  Yun Zhang,et al.  Wavelet based image fusion techniques — An introduction, review and comparison , 2007 .

[22]  Shutao Li,et al.  Multifocus image fusion using region segmentation and spatial frequency , 2008, Image Vis. Comput..

[23]  Aritra Dey,et al.  Face recognition using fusion of spatial and temporal features , 2018, 2018 Emerging Trends in Electronic Devices and Computational Techniques (EDCT).

[24]  Hassan Ghassemian,et al.  A review of remote sensing image fusion methods , 2016, Inf. Fusion.

[25]  Arif Mahmood,et al.  Multi-focus image fusion using Content Adaptive Blurring , 2019, Inf. Fusion.

[26]  Hannu Olkkonen,et al.  Gaussian Pyramid Wavelet Transform for Multiresolution Analysis of Images , 1996, CVGIP Graph. Model. Image Process..

[27]  David Kearney,et al.  Image fusion for uninhabited airborne vehicles , 2002, 2002 IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings..

[28]  Jiayi Ma,et al.  Infrared and visible image fusion methods and applications: A survey , 2018, Inf. Fusion.

[29]  Firooz Sadjadi,et al.  Comparative Image Fusion Analysais , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[30]  Jian Sun,et al.  Guided Image Filtering , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  R. J. Suthakar,et al.  Study of Image Fusion-Techniques , Method and Applications , 2014 .