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Image Matting Based Multi-Focus Image Fusion With Optimal Cluster Size

Image Matting Based Multi-Focus Image Fusion With Optimal Cluster Size

Rajesh Dharmaraj, Christopher Durairaj Daniel Dharmaraj
Copyright: © 2018 |Volume: 8 |Issue: 3 |Pages: 25
ISSN: 2155-6997|EISSN: 2155-6989|EISBN13: 9781522545736|DOI: 10.4018/IJCVIP.2018070103
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MLA

Dharmaraj, Rajesh, and Christopher Durairaj Daniel Dharmaraj. "Image Matting Based Multi-Focus Image Fusion With Optimal Cluster Size." IJCVIP vol.8, no.3 2018: pp.41-65. http://doi.org/10.4018/IJCVIP.2018070103

APA

Dharmaraj, R. & Dharmaraj, C. D. (2018). Image Matting Based Multi-Focus Image Fusion With Optimal Cluster Size. International Journal of Computer Vision and Image Processing (IJCVIP), 8(3), 41-65. http://doi.org/10.4018/IJCVIP.2018070103

Chicago

Dharmaraj, Rajesh, and Christopher Durairaj Daniel Dharmaraj. "Image Matting Based Multi-Focus Image Fusion With Optimal Cluster Size," International Journal of Computer Vision and Image Processing (IJCVIP) 8, no.3: 41-65. http://doi.org/10.4018/IJCVIP.2018070103

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Abstract

Image fusion is used to intensify the quality of images by combining two images of same scene obtained from different techniques. The present work deals with the effective extraction of pixel information from the source images that hold the key to multi focus image fusion. A solely vicinity-based image matting algorithm that relies on the close pixel clusters in the input images and their trimap, is presented in this article. The pixel cluster size, N plays a significant role in deciding the identity of the unknown pixel. The distance between each unknown pixel from foreground and background pixel clusters has been computed based on minimum quasi Euclidean distance. The minimum distance ratio gives the alpha value of each unknown pixel in the image. Finally, the focus regions are blend together to obtain the resultant fused image. On perceiving the results visually and objectively, it is concluded that proposed method works better in extracting the focused pixels and improving fusion quality, compared with other existing fusion methods.

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