The aim of image fusion is to combine appropriate information from two or more source images into one single image such that the single image is more informative than source images. Digital negative which is one of the spatial domain image enhancement techniques,enhances white or gray detail on dark regions, especially, when black areas are dominant in size. . Considering this, a method of image fusion is proposed, specifically for multi-focus images. Each of these images are fused with digital negative of each other for getting augmentation in white or gray detail on dark regions. Act of this method is evaluated with the help of fusion appraisal parameters like RMSE, PSNR, Mean Intensity value Mutual Information etc.

1. Shih –Gu Huang ,Wavelet for Image Fusion, Graduate Institute of Communication Engg & Deptof Electrical Engg. , National Taiwan University.
2. Parul Shah,Shabbir Merchant, Uday Desai, An efficient Adaptive Fusion scheme for multifocus images in Wavelet domain using statistical properties of neighborhood, 978-0-9824438-2-8/11/2011 IEEE
3. Disha Suru, Sunil Karamchandani, Contrast Enhancement using Image Fusion, MCTRGIT, International Conferenceon Advances in Computing and Information Technology, ICACIT 2014
4. Anju Rani, Gagandeep Kaul, Image Enhancement using Image Fusion, Vol 4 , issue 9,Sept 2014,IJARCSSE,pp-413-416
5. Vinod Saini,Tarun Gulati, A Comparative Study on Image Enhancement using Image Fusion, Vol 2,Issue 10Oct 12,IJARCSSE,pp. 141-145
6. Swati Khidse,Meghand Nagori, A Comparative study of Image Enhancement Techniques, IJCA,Vol 81, No. 15, Nov. 2013, pp. 28-32
7. Eyfin Nirmala, Dr. V. Vaidehi, Comparison of Pixel level and Feature level Image Fusion Methods, 978-9-38054416-8/15/2015/IEEE. , Second Interenational Conference on Computing for sustainable Global Development, pp743-748
8. Rania Hassen, Zhou Wang, Magadi M. A. Salama, Objectve quality assessment for multiexposure multifocus Image Fusion, IEEE transaction on Image Processing, Vol 24 ,No. 9,Sept 2015 ,pp. 2712-2724
9. Mounir Amraoui, Jafar Abouchaban,Larit Laboratory,Mohmed El Aroussi,978-1-4799-3824-7/14,2014/IEEE
10. Du Yong,Kim,Ba-Tuony, Vo,& Ba Ngu , Data Fusion in 3D vision using a RGB-D Data via Switching observationmodel and its applications to people tracking, 978-1-
11. 4799-0572-0113/2013/ICAIS2013,pp. 91-96Laith Hamid,Umit Aydin,Carsten Wolters,Ulrich Stephani, Michal Sinatchkin,Andreas Galka, MEG-EEGFusion Kalman Filtering within a source analysis Frame work,35th Annual International Confrerence of the IEEE EMBS,OSAKA, Japan3-7,July2013,pp 4819-4822
12. Mirjakar Pradnya, Raikar Sachin, Wavelet Based Image Fusion Techniques, 2013 ICISSP,pp77-81
13. Juan E Tapia,Claudio A Perz, Gender Classification Based on Fusion of DifferentSpatial Scale FeaturesSelected by Mutual InformationFrom Histogram of LBP, Intensity, and Shape, IEEE Transaction for Information and Security, Vol 8 ,No. 3 March 2013 , pp 488-499.
14. Mirjakar Pradnya,Sachin Ruikar,Image fusion based onStationary wavelet transform, Research paper, IJEARS/II/IV/July-Sept-2013/pp. 99-101
15. Borwonwatanadelok, Rattanapitak, Udomhunsakul,Multi-Focus Image Fusion based on Stationary Wavelet Transform and extended Spatial Frequency Measurement,2009 IEEE,DOI 10. 1109/ICECT. 2009. 94,77/pp. 77-81

Image Fusion Multi-focus Image Digital Negative Image Enhancement