Joint optimization of multispectral filter arrays and demosaicking for pathological images

TL;DR

This paper introduces a joint optimization method for multispectral filter arrays and demosaicking tailored for pathological images, improving spectral reconstruction accuracy while reducing capture time and costs.

Contribution

It proposes a novel joint optimization framework for MSFA spectral sensitivity and demosaicking specifically for pathology imaging, enhancing spectral fidelity.

Findings

Optimized spectral sensitivity reduces reconstruction error.

Improved spectral and RGB image quality over conventional methods.

Effective for pathology-specific multispectral imaging.

Abstract

A capturing system with multispectral filter array (MSFA) technology is proposed for shortening the capture time and reducing costs. Therein, a mosaicked image captured using an MSFA is demosaicked to reconstruct multispectral images (MSIs). Joint optimization of the spectral sensitivity of the MSFAs and demosaicking is considered, and pathology-specific multispectral imaging is proposed. This optimizes the MSFA and the demosaicking matrix by minimizing the reconstruction error between the training data of a hematoxylin and eosin-stained pathological tissue and a demosaicked MSI using a cost function. Initially, the spectral sensitivity of the filter array is set randomly and the mosaicked image is obtained from the training data. Subsequently, a reconstructed image is obtained using Wiener estimation. To minimize the reconstruction error, the spectral sensitivity of the filter array and the Wiener estimation matrix are optimized iteratively through an interior-point approach. The effectiveness of the proposed MSFA and demosaicking is demonstrated by comparing the recovered spectrum and RGB image with those obtained using a conventional method.