Inpainted Image Quality Evaluation Based on Saliency Map Features
Dariush Amirkhani, Azam Bastanfard · 2019
Digital image inpainting is one of the most important areas in image processing science. Digital image inpainting is a set of methods to inpaint or refill the damaged areas of the images. Given the increasing use of image inpainting and the lack of a good metric for evaluating image inpainting, there is a challenge in this field. In this study an objective evaluation method for image inpainting is developed. In the proposed method, first, 100 images were inpainted using exemplar-based algorithm, then, the saliency map and its complementary region in the original image are obtained and based on saliency map features, a new objective measure for evaluation of inpainted images is proposed. A term called compensation have been taken into account. To assess the performance of the proposed objective measure, inpainted images are also evaluated using a subjective test. The experiments demonstrate that the proposed objective measure correlates with qualitative opinion in a human observer study. Finally, the objective measure is compared against three other measures and the results show that our proposed objective measure is better than the others.