AI transforms image reconstruction

MR Image Reconstruction Exploiting Nonlinear Transforms

Figure 3: Image reconstruction results for 2D (upper row) and 3D (lower row) cardiac images comparing L1 minimization in wavelet and finite differences transform domains with the proposed projections in a nonlinear kernel feature space. Root mean squared errors are indicated in the insets. 4497 MR Image Reconstruction Exploiting Nonlinear Transforms Johannes F. M. Schmidt and Sebastian Kozerke ...

Iterative Tomographic Image Reconstruction Using Nonuniform Fast Fourier Transforms

Fourier-based reprojection methods have the potential to reduce the computation time in iterative tomographic image reconstruction. Interpolation errors are a limitation of Fourier-based reprojection methods. We apply a min-max interpolation method for the nonuniform fast Fourier transform (NUFFT) to minimize the interpolation errors. Numerical results show that the min-max NUFFT approach provi...

Evaluating Mutation Operators for Evolved Image Reconstruction Transforms

Various military systems require image and signal processing, often in noisy or bandwidth-limited situations. In this research, we employ genetic algorithms (GAs) to evolve forward and inverse transforms that reduce quantization error in reconstructed signals and images. The resulting transforms produce higher quality images than current waveletbased transforms at a given compression ratio and ...

Reconstruction-optimized lapped orthogonal transforms for robust image transmission

Wireless transmission of compressed visual information presents new challenges in image coding and reconstruction techniques. Unlike the traditional error-free media for which current coding standards have been designed, wireless channels do not offer guaranteed transmission, and data loss over such channels can result in catastrophic errors in the decoded visual information. Visual data, howev...

ISAR Signal Formation and Image Reconstruction as Complex Spatial Transforms