A quaternion-based spectral clustering method for color image segmentation

Xiang Li; Lianghai Jin; Hong Liu; Zeng He

doi:10.1117/12.901978

8 December 2011 A quaternion-based spectral clustering method for color image segmentation

Xiang Li, Lianghai Jin, Hong Liu, Zeng He

Proceedings Volume 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis; 800303 (2011) https://doi.org/10.1117/12.901978
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

Spectral clustering method has been widely used in image segmentation. A key issue in spectral clustering is how to build the affinity matrix. When it is applied to color image segmentation, most of the existing methods either use Euclidean metric to define the affinity matrix, or first converting color-images into gray-level images and then use the gray-level images to construct the affinity matrix (component-wise method). However, it is known that Euclidean distances can not represent the color differences well and the component-wise method does not consider the correlation between color channels. In this paper, we propose a new method to produce the affinity matrix, in which the color images are first represented in quaternion form and then the similarities between color pixels are measured by quaternion rotation (QR) mechanism. The experimental results show the superiority of the new method.

Citation Download Citation

Xiang Li, Lianghai Jin, Hong Liu, and Zeng He "A quaternion-based spectral clustering method for color image segmentation", Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 800303 (8 December 2011); https://doi.org/10.1117/12.901978

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