Better Guiding the Guided Range Image Filter for Range-Image Super-resolution

Abstract

Range-image super-resolution has evolved in recent years to improve the images acquired by low-resolution rangecameras. In this regard, some local filtering based approaches are quite popular as they achieve reasonable quality rangeimages while maintaining high computational efficiency. In this work, we propose a novel and improved local approach, which is inspired by the popular Guided Image Filtering method, that employs information from an associated color image for the task of range-image super-resolution. Our approach accounts for consideration of the content of both color image and range image explicitly, to drive the enhancement process. We show that our filter reduces noise for noisy range-images along with better edge enhancement, especially for higher up-sampling factors. Our experimentation also demonstrate that our approach performs better than other prominent local filtering approaches both in terms of depth precision and spatial resolution without any considerable increase in computational time.