The popularity of low-cost RGB-D scanners is increasing on a daily basis. Nevertheless, existing

scanners often cannot capture subtle details in the environment. We present a novel method to

enhance the depth map by fusing the intensity and depth information to create more detailed

range profiles. The proposed framework assumes that color and depth cues are taken from

a calibrated system, therefore they can be easily aligned. A normal map is estimated from a

smoothed version of the depth input. The acquired normal map together with the color image

and depth profile are then used to compute the scene lighting. The lighting model we use can

handle natural scene illumination. It recovers the shading of the image and then accounts for

albedos, shadows, and specularities. We then integrate the lighting model in a shape from

shading like technique to improve the visual fidelity of the reconstructed object. Unlike previous

efforts in this domain, the detailed geometry is calculated directly, without the need to explicitly

find and integrate surface normals. In addition, the proposed method operates four orders of

magnitude faster than the state of the art. Qualitative and quantitative visual and statistical

evidence support the improvement in the depth obtained by the suggested method.