<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.</p></abstract>

In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.

Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, China

School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Nanchang 330013, China

College of Biomedical Engineering, South-Central University for Nationalities, Wuhan 430074, China

Measurement Science Review

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform...

Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

Online veröffentlicht: 08. Mai 2014

Seitenbereich: 102 - 108

Eingereicht: 30. Juli 2013

Akzeptiert: 24. März 2014

DOI: https://doi.org/10.2478/msr-2014-0014

Schlüsselwörter
Multi-focus image fusion, wavelet coefficients, image sharpness, energy

© by Shuying Huang

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

Online veröffentlicht: 08. Mai 2014

Seitenbereich: 102 - 108

Eingereicht: 30. Juli 2013

Akzeptiert: 24. März 2014

DOI: https://doi.org/10.2478/msr-2014-0014

SchlüsselwörterMulti-focus image fusion, wavelet coefficients, image sharpness, energy

© by Shuying Huang

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Schlüsselwörter
Multi-focus image fusion, wavelet coefficients, image sharpness, energy