Multi-Focus Color Image Fusion Based on Quaternion Multi-Scale Singular Value Decomposition

• Published in: Frontiers in neurorobotics 2021-06, Vol.15, p.695960-695960
• Main Authors: Wan, Hui, Tang, Xianlun, Zhu, Zhiqin, Xiao, Bin, Li, Weisheng
• Format: Article
• Language: English
• Subjects: image fusion; multi-focus color image; multi-scale decomposition; Neuroscience; quaternion; singular value decomposition
• ISSN: 1662-5218; 1662-5218
• DOI: 10.3389/fnbot.2021.695960

Most existing multi-focus color image fusion methods based on multi-scale decomposition consider three color components separately during fusion, which leads to inherent color structures change, and causes tonal distortion and blur in the fusion results. In order to address these problems, a novel fusion algorithm based on the quaternion multi-scale singular value decomposition (QMSVD) is proposed in this paper. First, the multi-focus color images, which represented by quaternion, to be fused is decomposed by multichannel QMSVD, and the low-frequency sub-image represented by one channel and high-frequency sub-image represented by multiple channels are obtained. Second, the activity level and matching level are exploited in the focus decision mapping of the low-frequency sub-image fusion, with the former calculated by using local window energy and the latter measured by the color difference between color pixels expressed by a quaternion. Third, the fusion results of low-frequency coefficients are incorporated into the fusion of high-frequency sub-images, and a local contrast fusion rule based on the integration of high-frequency and low-frequency regions is proposed. Finally, the fused images are reconstructed employing inverse transform of the QMSVD. Simulation results show that image fusion using this method achieves great overall visual effects, with high resolution images, rich colors, and low information loss.