This article proposes a new method for the fast and efficient calculation of 3D Tchebichef moments,which are an essential tool for the characterization and analysis of 3D objects. This method integrates the Kronecker tensor product to the computation of 3D Tchebichef moments for higher orders with the advantage of being parallelizable. The experimental results clearly show the benefits and efficacy of the proposed method compared to existing methods. Keywords 3D discrete orthogonal Tchebichef moments • Fast computation • 3D image reconstruction • High-order moments • Kronecker tensor product
Image reconstruction can help to determine how well an image may be characterized by a small finite set of its moments. Also, we can identify the number of descriptors needed to describe an image. In this work, we present a comparative analysis using different set of discrete orthogonal moments in terms of normalized image reconstruction error (NIRE). Color image reconstruction is performed with different color channels and various orders of different discrete orthogonal moments. Finally the results obtained by the reconstruction of three color images with different families of orthogonal moments and an error analysis to compare their capacity of description are presented, also the conclusions obtained from this work are presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.