Assessment of color image fusion algorithms based on quaternion singular value decomposition

Yuqing Wang; Ming Zhu; Haochen Pang; Yong Wang

doi:10.1117/12.833901

30 October 2009 Assessment of color image fusion algorithms based on quaternion singular value decomposition

Yuqing Wang, Ming Zhu, Haochen Pang, Yong Wang

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74981Y (2009) https://doi.org/10.1117/12.833901
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

In this paper, a new approach to objectively assess the performance of image fusion algorithms is proposed. It is based on the quaternion representation for the structural information of color images. Quaternions are used to encode the pixels of a color image into a quaternion matrix. Local variance of the luminance layer of color image is taken as the real part of a quaternion, then the three RGB channels of the color image are encoded into the three imaginary parts of the quaternion. The angle between the singular value feature vectors of the quaternion matrices corresponding to the source image and the fused image is used to measure the structural similarity of them. Different weight is given to the source images by using variance. The experiment results show that the proposed assessment method is consistent with the HVS. The color information of a color image can be fully used by this method. It can give an accurate assessment result for each fusion algorithm by using the source images and the fused image.

Citation Download Citation

Yuqing Wang, Ming Zhu, Haochen Pang, and Yong Wang "Assessment of color image fusion algorithms based on quaternion singular value decomposition", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981Y (30 October 2009); https://doi.org/10.1117/12.833901

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KEYWORDS

Image fusion

Image quality

Matrices

Discrete wavelet transforms

Eye

Image sensors

Infrared imaging

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