Multi-Focus Image Fusion using Non-Local Mean Filtering and Stationary Wavelet Transform
Kapil Joshi1, N.K.Joshi2, Manoj Diwakar3, A.N. Tripathi4, Himanshu Gupta5

1Kapil Joshi, Department of CSE, Uttaranchal University, Dehradun, India.
2N. K. Joshi, Department of CSE, Uttaranchal University, Dehradun, India.
3Manoj Diwakar, Department of CSE, Graphic Era University, Dehradun, India.
4A. N. Tripathi, Department of CSE, University of Petroleum and Energy Studies, Dehradun, India.
5Himanshu Gupta, Department of CSE, College of Engineering Roorkee, Roorkee, India. 

Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 344-350 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4123119119/2019©BEIESP | DOI: 10.35940/ijitee.A4123.119119
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Abstract: Today’s research era, image fusion is a actual step by step procedure to develop the visualization of any image. It integrates the essential features of more than a couple of images into a individual fused image without taking any artifacts. Multifocus image fusion has a vital key factor in fusion process where it aims to increase the depth of field using extracting focused part from different multiple focused images. In this paper multi-focus image fusion algorithm is proposed where non local mean technique is used in stationary wavelet transform (SWT) to get the sharp and smooth image. Non-local mean function analyses the pixels belonging to the blurring part and improves the image quality. The proposed work is compared with some existing methods. The results are analyzed visually as well as using performance metrics.
Keywords:  Image Fusion, Stationary Wavelet Transforms (SWT), Non-Local Mean Filter (NLM).
Scope of the Article: Image Processing and Pattern Recognition