Multispectral image enhancement by spectral shifting

Pinky A. Bautista; Yukako Yagi

doi:10.1117/12.910060

28 February 2012 Multispectral image enhancement by spectral shifting

Pinky A. Bautista, Yukako Yagi

Proceedings Volume 8214, Advanced Biomedical and Clinical Diagnostic Systems X; 82140K (2012) https://doi.org/10.1117/12.910060
Event: SPIE BiOS, 2012, San Francisco, California, United States

Abstract

A multispectral enhancement method that preserves the natural color of the background pixels was previously proposed. In such method, the band for enhancement was identified from the N-band spectral residual-error of the objects of interest. The spectral residual-error is determined by taking the difference between the original spectrum of the pixel and its estimate using M<<N principal components in principal component analysis (PCA). However, for stained histopathology images where staining variations do exist even among tissue sections the band for enhancement could vary. In this work, we introduced a modification to the previously proposed multispectral enhancement method such that the band for enhancement could be specified independent of the spectral residualerror configurations. In the proposed modification the original spectral transmittance of the pixels at each band are shifted by the product between the spectral residual-error coefficient, which is the most dominant PC coefficient of the spectral error, of the pixel and the weighting factor assigned by the user to each band. Results of our experiments on H&E stained sections of liver tissue show that the proposed modification delivers more consistent enhancement results compared to the previously proposed methods, especially when the band for enhancement varies.

Citation Download Citation

Pinky A. Bautista and Yukako Yagi "Multispectral image enhancement by spectral shifting", Proc. SPIE 8214, Advanced Biomedical and Clinical Diagnostic Systems X, 82140K (28 February 2012); https://doi.org/10.1117/12.910060

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KEYWORDS

Image enhancement

Transmittance

Tissues

Multispectral imaging

Collagen

Principal component analysis

Visualization

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