Abstract. Motion estimation is essential in a variety of image processing and computer vision tasks, like video coding, tracking, directional filtering and denoising, scene analysis, etc. Transparent motions are additive or multiplicative superpositions of moving patterns and occur due to reflections, semi-transparencies, and partial occlusions. The estimation of transparent motions remained a challenging nonlinear problem. We here first linearize the problem in a way which makes it accessible to the known methods used for the estimation of single motions, such as structure tensor, regularization, block matching, Fourier methods, etc. Theoretically, our solution does not limit the number of transparent layers. Finally, we present a way to categorize different transparent motion patterns based on the rank of a generalized structure tensor. 1

Mathematical methods for time series analysis and digital image processing