The capability to capture depth information of static real-world objects has achieved increased importance in many fields of application

such as manufacturing and prototyping

as well as in the design of virtual worlds for movies and games. A time-of-flight camera can conveniently obtain scene depth images. However

the resolution of a depth image is low and cannot satisfy actual requirements because of hardware limitations. Stereo matching algorithms are classical methods used to obtain depth images

but they are significantly limited in practical applications because of the occlusion between left and right images and the non-textured area. In this study

we propose a novel method to obtain a high-resolution

high-quality depth map by combining stereo matching with the use of a time-of-flight camera.We formulate a non-local adaptive weighting filter and obtain an initial high-resolution depth map using the low-resolution depth map from the time-of-flight camera. Then

we use the initial depth map and a local stereo matching algorithm to construct adaptive weights for stereo matching and obtain a raw depth map. Given that discontinuities within a range and coloring tend to coalign

we construct a local weighting filter using the raw depth map and the features of a high-resolution color image to reinforce the preservation of fine details. Experiments demonstrate that our approach can obtain an excellent high-resolution range image. Comparison experiments on peak signal-to-noise ratio and error rate show that our method can reconstruct high-quality depth maps. The proposed method can produce sharper edges and more accurate details compared with other state-of-the-art approaches.