Comparison of Metrics for Colorized Image Quality Evaluation

Colorization is a process of converting grayscale images into visually acceptable colorized images. It is a complex problem because no unique solution exists, i.e., the objects within the image cannot be associated with one color only. Colorized image quality assessment is also a complex problem because in real life the reference image for comparison with colorized results does not exist. The main purpose of colorization is convincing the observer in the credibility of the colorized image, disregarding color accuracy. For that reason, both subjective and objective evaluation of colorization results show imperfections. In this paper, the objective quality evaluation of colorized images has been conducted with five existing metrics and one new metric. The database of colorized images has been obtained by deep learning colorization methods. Based on the conducted subjective testing, a correlation between objective metrics and subjective grades has been determined. The results indicate that the improvement of objective metrics for the evaluation of colorized images is needed.