Image capture and fusion of 3d surface texture using wavelet transform

Image fusion is a process, in which the multiple images of the scene are combined into a single fused image in order to preserve the full content of the scene and also retain the important features from each original image respectively. In this paper, we propose a novel wavelet transform based approach to achieve the image capture and fusion of 3D surface texture. There are two components in real-world surface textures — rough surface geometry properties and its reflectance properties. 3D surface textures are different from 2D textures as their appearing can vary dramatically with different illumination conditions. A novel wavelet transform based scheme is employed in this paper. Every saliency of wavelet decomposition coefficient is measured in each original input image. The saliency value visually reflects the meaningful contents of the wavelet decomposition coefficients, and it’s consistent with human visual perception too. This novel scheme aims to preserve the full content values and retain the meaningful information with respect to human visualization and perception. In addition, the fusion of 3D surface texture composes both the albedo (e.g. color) and geometry properties (e.g. height or gradient map), therefore a new fusion image of the 3D surface texture under arbitrary illuminant direction can be generated. Experimental results show that the proposed approach not only captures and fusions 3D surface texture under arbitrary illumination directions, but also has the ability to retain the surface geometry structures and preserve perceptual features in the image.