Resolution Enhancement of Range Images via Color-Image Segmentation
This addresses resolution enhancement for range imaging, but it is incremental as it builds on a previously reported method.
The paper tackles super-resolution of range images by interpreting low-resolution images as sparse samples and using a single registered color image to reconstruct dense range data, achieving good localization accuracy for large factors like 4.
We report a method for super-resolution of range images. Our approach leverages the interpretation of LR image as sparse samples on the HR grid. Based on this interpretation, we demonstrate that our recently reported approach, which reconstructs dense range images from sparse range data by exploiting a registered colour image, can be applied for the task of resolution enhancement of range images. Our method only uses a single colour image in addition to the range observation in the super-resolution process. Using the proposed approach, we demonstrate super-resolution results for large factors (e.g. 4) with good localization accuracy.