Color filter arrays revisited - Evaluation of Bayer pattern interpolation for industrial applications

Modern industrial cameras mainly use the Bayer pattern as color filter array (CFA). However, this filtering limits the resolution of the color space. As interpolation methods cannot reconstruct the original image perfectly, they have to be optimized for a specific application. Therefore, the interpolation should match the purpose of the image processing system. Many standard algorithms are optimized for the subjective impression of a human observer which is not necessarily ideal for industrial applications. This paper introduces a new methodology for evaluating interpolation algorithms in industrial applications. For this purpose, a new dataset based on printed circuit boards as representatives for objects in industrial application is introduced. It shows many distinct features which are typical for industrial scenarios such as high contrast object edges, highly reflective materials and low variety of surface colors. Furthermore, two new error measures based on edge accuracy are presented which are tailored to many measurement tasks which employ edges. It can be shown in an evaluation of common CFA interpolation algorithms that these new error measures are better suited to identify the best interpolation algorithm for retaining edge accuracy than conventional error measures.