Publication Type:

Journal Article

Source:

Lecture Notes in Computational Vision and Biomechanics, Springer Netherlands, Volume 28, p.579-592 (2018)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042436885&doi=10.1007%2f978-3-319-71767-8_50&partnerID=40&md5=dfbf26c266c7d1ebd346977af562c2ba

Abstract:

<p>This work focuses on an optimum process of image fusion on multiple focus images using an optimization algorithm viz., Differential Evolution (DE) algorithm. The input image is divided into regions and sharper regions are selected from these two images. The selected clear blocks are used for constructing final resultant image. The main purpose of using differential evolution algorithm is to find out optimum block size, which is more useful during division of image rather than fixed block size. And also, this work compares different variants of differential evolution algorithm based image fusion to find out which one will be suitable for getting more focused image. The major focus of the research is finding out which type of differential evolution algorithm is best suitable for almost all type of images. Block based and pixel based method are used together to achieve a better resultant image. Performance of fused image is calculated using image quality measures and found out better fusion method, which can be used in almost all situations. © 2018, Springer International Publishing AG.</p>

Notes:

cited By 0

Cite this Research Publication

K. C. Haritha and Thangavelu, S., “Multi focus region-based image fusion using differential evolution algorithm variants”, Lecture Notes in Computational Vision and Biomechanics, vol. 28, pp. 579-592, 2018.

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