Here we introduce an image fusion method based on color spaces to combine different Mueller matrix derived parameters to provide multi-dimensional structural information pixel by pixel in a single polarization staining image. Then, in order to quantitatively analyze the texture characteristics of the polarization staining images for different structures, the Tamura image processing and the gray level co-occurrence matrix (GLCM) methods are adopted to provide various evaluation indices after the images segmentations. The experimental results confirm that the information provided by the polarization staining images based on different Mueller matrix derived parameters can be used for accurate tissue structures discrimination.
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