The image moment method for the limited range CT image reconstruction and pattern recognition

Image reconstruction from limited range projections using orthogonal moments

“…In real situations, projections from certain views are known while projections from other views are unknown. To distinguish them, we adopt here the same terminology used in [10]. The projections are called given projections if the views are given views; the unknown projections correspond to the projections whose views are unknown.…”

“…2. For comparison, the real projections (computed by a projection simulation program) and the estimation results from these views using the geometric moment-based method proposed by Wang and Sze [10] are also shown in this figure. Fig.…”

“…Basu and Bresler [8,9] discussed the problem of recovering the view angles using moments of the projections. Wang and Sze [10] proposed an approach based on the relationship between the projection moments and the image moments to reconstruct the CT images from limited range projections. In the Wang's algorithm, the geometric moments were used and interesting results have been obtained.…”

Full-Field Optical Coherence Tomography Using Galvo Filter-Based Wavelength Swept Laser

“…As a result, surface profile measurement has become an important issue in industrial inspection processes to reduce the defect rate and to fulfill the consumers’ demand. Many nondestructive three-dimensional (3D) surface profiling techniques have been developed to monitor product quality and to improve process efficiency [1,2,3,4]. Furthermore, different optical inspection methods have been proposed for 3D surface profile imaging with cost-effective, nondestructive, noncontact, high-speed, and high-accuracy solutions [5,6,7,8,9].…”

A General Framework for Computation of Biomedical Image Moments

“…The most well known orthogonal moment families are: Zernike, Pseudo-Zernike, Legendre, Fourier-Mellin, Tchebichef, Krawtchouk, dual Hahn moments, with the last three ones belonging to the discrete type moments since they are defined directly to the image coordinate space, while the first ones are defined in the continue space. Recently, there is an increased interest on applying image moments in biomedical imaging, with the reconstruction of medical images (Dai et al, 2010;Papakostas et al, 2009b;Shu et al, 2007;Wang & Sze, 2001) and the description of image's parts with particular properties (Bharathi & Ganesan, 2008;Iscan et al, 2010;Li & Meng, 2009;Liyun et al, 2009) by distinguishing diseased areas from the healthy ones, being the most active research directions the scientists work with. Therefore, a method that computes fast and accurate the orthogonal moments of a biomedical image is of great importance.…”