Quality Assessment of 2.5D Prints Using 2D Image Quality Metrics

Abstract

Quality assessment is an important aspect in a variety of application areas. In this work, the objective quality assessment of 2.5D prints was performed. The work is done on camera captures under both diffuse (single-shot) and directional (multiple-shot) illumination. Current state-of-the-art 2D full-reference image quality metrics were used to predict the quality of 2.5D prints. The results showed that the selected metrics can detect differences between the prints as well as between a print and its 2D reference image. Moreover, the metrics better detected differences in the multiple-shot set-up captures than in the single-shot set-up ones. Although the results are based on a limited number of images, they show existing metrics’ ability to work with 2.5D prints under limited conditions.

Colourlab Image Database: Geometric Distortions

“…A plethora of objective Image Quality Metrics (IQMs) have been proposed in the literature [1], with the goal to complement or replace subjective assessment. These have been suggested for a number of applications, such as printing [2,3], gamut mapping [4], tone mapping [5], and 360 degree images [6]. To evaluate the performance of IQMs, datasets containing distorted images and their respective subjective quality scores have been introduced [7,8,9,10].…”