Title: Optimal wavelet-based multi-modal medical image fusion with quantitative analysis for colour images using different colour models

Authors: Rekha R. Nair; Tripty Singh

Addresses: Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India Fax: +91-(80)-2844-0092 ' Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India Fax: +91-(80)-2844-0092

Abstract: Colour is the component generally used to discriminate and recognise information and it is also considered as one of the most important aspects of vision. Abundant of information contained in the colour image can be utilised for multiple purposes applications such as image analysis, object identification and extraction of powerful details. This paper proposes an optimal wavelet colour image fusion (OWCIF) algorithm for multi-modal medical images that can work with source images of any size. The proposed algorithm works with greyscale and colour images. OWCIF is composed of the logarithmic and wavelet domain of the transformed colour model of source images. The local energy fusion rule provides sharp edge details. The experiment is conducted on eight colour models with four different proposed algorithms. The evaluation of the OWCIF algorithm performance is demonstrated with the help of four sets of colour standard dataset images. The images used in this work are MRA, MR-T1, CT, PET, MRI, and SPECT. Subjective evaluation of the fusion result is carried out by the assistance of expert radiologists. The four proposed OWCIF algorithms compared with each other to identify better algorithms and colour models for the set of given images.

Keywords: medical image fusion; logarithmic wavelet; colour model; whale optimisation algorithm.

DOI: 10.1504/IJBET.2022.126496

International Journal of Biomedical Engineering and Technology, 2022 Vol.40 No.3, pp.262 - 288

Received: 27 Jan 2020
Accepted: 01 Jun 2020
Published online: 27 Oct 2022 *

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