The multifocus images fusion based on a generative gradient map

The limitation of camera lens is inability to make focus region for whole scene in one shot image. The camera creates one focus object for one image. It is needed several images to get many focus objects of the scene. It makes difficult to read many focus objects from several images. Multifocus imag...

Full description

Bibliographic Details
Main Authors: Ismail, ., Kamarul Hawari, Ghazali
Format: Conference or Workshop Item
Language:English
English
Published: Springer 2020
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/37773/
http://umpir.ump.edu.my/id/eprint/37773/1/The%20multifocus%20images%20fusion%20based%20on%20a%20generative%20gradient%20map.pdf
http://umpir.ump.edu.my/id/eprint/37773/2/The%20Multi%20focus%20Images%20Fusion%20Based_FULL.pdf
_version_ 1848825341089415168
author Ismail, .
Kamarul Hawari, Ghazali
author_facet Ismail, .
Kamarul Hawari, Ghazali
author_sort Ismail, .
building UMP Institutional Repository
collection Online Access
description The limitation of camera lens is inability to make focus region for whole scene in one shot image. The camera creates one focus object for one image. It is needed several images to get many focus objects of the scene. It makes difficult to read many focus objects from several images. Multifocus image fusion is a process of combining many focus objects from several images into one image. This operation gives easier way to read focus information from many images clearer. It commonly needed in medical examination, robotics and bioinformatics fields. The clearness information enables machine, computer and human understand the image better and prevents any mistake. In an image, the clear object is only located in focus region. In order to generate all objects in focus region, the multi focus images will be fused into fused image. The methods generally use complicated mathematic equation and hard algorithm. In addition to handle the problem, we design a simple way and have accurate output. Our method is the multifocus image fusion based on generative gradient map. By generative gradient map, it quickly determines the initial prediction of focus region precisely. The Generative gradient map is the external information, generated from gradient of blurred random number image. This procedure substitutes complicated mathematical equations or hard algorithm sequence implementation. Finally, our algorithm able to produces a fused image with high quality. The assessment of our method is according to Mutual Information and Structure Similarity parameter.
first_indexed 2025-11-15T03:27:23Z
format Conference or Workshop Item
id ump-37773
institution Universiti Malaysia Pahang
institution_category Local University
language English
English
last_indexed 2025-11-15T03:27:23Z
publishDate 2020
publisher Springer
recordtype eprints
repository_type Digital Repository
spelling ump-377732023-06-06T07:46:58Z http://umpir.ump.edu.my/id/eprint/37773/ The multifocus images fusion based on a generative gradient map Ismail, . Kamarul Hawari, Ghazali TK Electrical engineering. Electronics Nuclear engineering The limitation of camera lens is inability to make focus region for whole scene in one shot image. The camera creates one focus object for one image. It is needed several images to get many focus objects of the scene. It makes difficult to read many focus objects from several images. Multifocus image fusion is a process of combining many focus objects from several images into one image. This operation gives easier way to read focus information from many images clearer. It commonly needed in medical examination, robotics and bioinformatics fields. The clearness information enables machine, computer and human understand the image better and prevents any mistake. In an image, the clear object is only located in focus region. In order to generate all objects in focus region, the multi focus images will be fused into fused image. The methods generally use complicated mathematic equation and hard algorithm. In addition to handle the problem, we design a simple way and have accurate output. Our method is the multifocus image fusion based on generative gradient map. By generative gradient map, it quickly determines the initial prediction of focus region precisely. The Generative gradient map is the external information, generated from gradient of blurred random number image. This procedure substitutes complicated mathematical equations or hard algorithm sequence implementation. Finally, our algorithm able to produces a fused image with high quality. The assessment of our method is according to Mutual Information and Structure Similarity parameter. Springer 2020 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/37773/1/The%20multifocus%20images%20fusion%20based%20on%20a%20generative%20gradient%20map.pdf pdf en http://umpir.ump.edu.my/id/eprint/37773/2/The%20Multi%20focus%20Images%20Fusion%20Based_FULL.pdf Ismail, . and Kamarul Hawari, Ghazali (2020) The multifocus images fusion based on a generative gradient map. In: Lecture Notes in Electrical Engineering; 5th International Conference on Electrical, Control and Computer Engineering, InECCE 2019 , 29 July 2019 , Kuantan. 401 -413., 632 (238739). ISSN 1876-1100 ISBN 978-981152316-8 (Published) https://doi.org/10.1007/978-981-15-2317-5_34
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ismail, .
Kamarul Hawari, Ghazali
The multifocus images fusion based on a generative gradient map
title The multifocus images fusion based on a generative gradient map
title_full The multifocus images fusion based on a generative gradient map
title_fullStr The multifocus images fusion based on a generative gradient map
title_full_unstemmed The multifocus images fusion based on a generative gradient map
title_short The multifocus images fusion based on a generative gradient map
title_sort multifocus images fusion based on a generative gradient map
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/37773/
http://umpir.ump.edu.my/id/eprint/37773/
http://umpir.ump.edu.my/id/eprint/37773/1/The%20multifocus%20images%20fusion%20based%20on%20a%20generative%20gradient%20map.pdf
http://umpir.ump.edu.my/id/eprint/37773/2/The%20Multi%20focus%20Images%20Fusion%20Based_FULL.pdf