Open access peer-reviewed Edited Volume

Image Fusion - Design Architectures and Applications

Yan Chai Hum

Universiti Tunku Abdul Rahman

As a researcher in artificial intelligence and computer vision, Dr. Hum has filed 18 patents and won a number of research competition awards in Malaysia while working as a senior engineer in the national ICT research center, MIMOS, and at the Universiti Tunku Abdul Rahman.


Sensors Modelling Decision Levels High-pass Filtering Technique IHS Transform-based Image Fusion PCA-based Image Fusion Remote Sensing Satellite Imaging Information Theory Features Structural Similarity Hybrid Image Fusion Approaches Artificial Intelligence

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About the book

This book introduces the basic theories and applications of image fusion in various fields. Recent advancement of sensor technology accelerates the development of image fusion. The main purpose of fusing images is to aggregate information from various sources such that the fused image contains pertinent details from different images as compared to a single image from either source. The advantage of fusing images into a single image is invariably associated with data reduction while retaining important information.

This book will introduce this topic from explaining the current trend of image fusion, fundamental theories of applying image fusion, standard image fusion methods to the specific applications of image fusion in different fields especially the vast utility of image fusion in the field of medicine, remote sensing and satellite imaging. This book can serve as a basic reference book for undergraduate students as well as engineers and academic researchers that require the knowledge of image fusion algorithms.

Publishing process

Book initiated and editor appointed

Date completed: July 14th 2020

Applications to edit the book are assessed and a suitable editor is selected, at which point the process begins.

Chapter proposals submitted and reviewed

Deadline Extended: Open for Submissions

Potential authors submit chapter proposals ready for review by the academic editor and our publishing review team.

Approved chapters written in full and submitted

Deadline for full chapters: October 3rd 2020

Once approved by the academic editor and publishing review team, chapters are written and submitted according to pre-agreed parameters

Full chapters peer reviewed

Review results due: December 22nd 2020

Full chapter manuscripts are screened for plagiarism and undergo a Main Editor Peer Review. Results are sent to authors within 30 days of submission, with suggestions for rounds of revisions.

Book compiled, published and promoted

Expected publication date: February 20th 2021

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About the editor

Yan Chai Hum

Universiti Tunku Abdul Rahman

Dr. Hum Yan Chai is a researcher in artificial intelligence and computer vision. He received his B.Eng degree in biomedical engineering from the Universiti Teknologi Malaysia (UTM) in 2010. He graduated with a Ph.D. degree in 2013 from UTM for his research topic related to the application of artificial intelligence in medical image analysis. His research interests include computer vision, machine learning, data mining, pattern recognition, multiple-objectives optimization, signal processing, and medical image processing. After completing his Ph.D., he worked as a senior engineer in the national ICT research center, MIMOS, for three years. During his tenure there, he was assigned to improve the algorithm quality of video analytics related to computer vision and to analyze the performance of various types of existing solutions. Dr. Hum (MIET) registered as a Chartered Engineer (UK) and Professional Engineer (BEM) in 2016. He is passionate about conducting research and has published more than 30 international research articles, authored 5 books related to his research, filed 18 patents, and won a number of research competition awards in Malaysia. He is currently serving as an Assistant Professor in the Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman.

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