Reconstructing Textureless Objects Image Enhancement for 3D Reconstruction of Weakly-Textured Surfaces

Photogrammetric techniques for 3D reconstruction of weakly-textured surfaces are challenging. This paper proposes a new method to enhance image-based 3D reconstruction of weakly-textured surfaces. The idea behind it is to enhance the contrast of images, especially in weakly-textured regions, before feeding them to the reconstruction pipeline. Images contrast is enhanced using a recently proposed approach for noise reduction. The dynamic range of the generated denoised-images has to be squeezed to the limited 8-bit range that is used by the standard 3D reconstruction techniques. Dynamic range squeezing is a very critical process and can lead to information losses, since many levels in the original range will no longer be available in the limited target range. To this end, this paper proposes a new tone-mapping approach that is based on Contrast Limited Adaptive Histogram Equalization (CLAHE). It amplifies the local contrast adaptively to effectively use the limited target range. At the same time, it uses a limit to prevent local noise from being amplified. Using our approach leads to a significant improvement of up to 400% in the completeness of the 3D reconstruction.