A Hierarchical Superpixel-Based Approach for DIBR View Synthesis

View synthesis allows observers to explore static scenes using aligned color images and depth maps captured in a preset camera path. Among the options, depth-image-based rendering (DIBR) approaches have been effective and efficient since only one pair of color and depth map is required, saving storage and bandwidth. The present work proposes a novel DIBR pipeline for view synthesis that properly tackles the different artifacts that arise from 3D warping, such as cracks, disocclusions, ghosts, and out-of-field areas. A key aspect of our contributions relies on the adaptation and usage of a hierarchical image superpixel algorithm that helps to maintain structural characteristics of the scene during image reconstruction. We compare our approach with state-of-the-art methods and show that it attains the best average results in two common assessment metrics under public still-image and video-sequence datasets. Visual results are also provided, illustrating the potential of our technique in real-world applications.

Automated summary

The study introduces a novel DIBR pipeline for view synthesis that effectively tackles artifacts arising from 3D warping, while maintaining structural characteristics of the scene through an image superpixel algorithm. Comparative analysis demonstrates superior performance in average results across common assessment metrics, with visual results highlighting the technique's potential for real-world applications.