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2018 | OriginalPaper | Buchkapitel

Multi-focus Image Fusion Using Deep Belief Network

verfasst von : Vaidehi Deshmukh, Arti Khaparde, Sana Shaikh

Erschienen in: Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1

Verlag: Springer International Publishing

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Abstract

Multi-focus images may be fused to get the relevant information of a particular scene. Due to the limited depth of field of a convex lens of a camera, some objects in the image may not be focused. These images are fused to get all-in-focus image. This paper proposes an innovative way to fuse multi-focus images. The proposed algorithm calculates weights indicating the sharp regions of input images with the help of Deep Belief Network (DBN) and then fuses input images using weighted superimposition fusion rule. The proposed algorithm is analyzed and examined using various parameters like entropy, mutual information, SSIM, IQI etc.

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Titel: Multi-focus Image Fusion Using Deep Belief Network
verfasst von: Vaidehi Deshmukh
Arti Khaparde
Sana Shaikh
Verlag: Springer International Publishing
Buch: Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1
Print ISBN: 978-3-319-63672-6

Electronic ISBN: 978-3-319-63673-3

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-63673-3_28

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