Inverse Surfacelet Transform for Image Reconstruction With Prior Knowledge
Wei Huang, Yan Wang, David W. Rosen · 2013
Image reconstruction is the transformation process from some other data forms to image pixels. It can be utilized as a method to retrieve material composition information in materials characterization and design. In our previous work, a so-called surfacelet model was proposed to construct the geometric boundary and internal material distribution of heterogeneous materials at the same time. A surfacelet transform is able to efficiently represent boundary information in images of materials. In this paper, new constrained-conjugate-gradient-based image reconstruction methods are proposed as the inverse surfacelet transform. With geometric constraints on internal boundaries of materials, the proposed method is able to automatically identify the locations and orientations of the internal boundaries based on prior knowledge so as to reconstruct material composition with incomplete data.