Optimal Spectral Sensitivity of Multispectral Filter Array for Pathological Images

TL;DR

This paper introduces an optimized multispectral filter array design tailored for pathological images, improving spectral reconstruction accuracy while reducing capturing time and costs.

Contribution

It proposes a novel pathology-specific MSFA optimization method that minimizes reconstruction error through iterative spectral sensitivity adjustments.

Findings

Optimized MSFA improves spectral reconstruction accuracy.

The method reduces capturing time and costs.

Enhanced image quality in pathological imaging.

Abstract

A capturing system with multispectral filter array (MSFA) technology has been researched to shorten the capturing time and reduce the cost. In this system, the mosaicked image captured by the MSFA is demosaicked to reconstruct multispectral images (MSIs). We focus on the spectral sensitivity design of a MSFA in this paper and propose a pathology-specific MSFA. The proposed method optimizes the MSFA by minimizing the reconstruction error between training data of a pathological tissue and a demosaicked MSI under a cost function. Firstly, the spectral sensitivities of the filter array are set randomly, and the mosaicked image is obtained from the training data and the filter array. Then, a reconstructed image is obtained by Wiener estimation. The spectral sensitivities of the filter array are optimized iteratively by an interior-point approach to minimize the reconstruction error. We show the effectiveness of the proposed MSFA by comparing the recovered spectrum and RGB image with a conventional method.