Feature-preserving lossy image compression using nonlinear PDEs
In this report, we propose combining the Total Variation denoising method with the high loss wavelet compression for high noise level images. Numerical experiments show that TV-denoising can bring more wavelet coefficients closer to zero thereby making the compression more efficient while the salient features (edges) of the images can still be retained.
An approach for estimating the parameters of mixed Weibull distributions is presented. The problem is formulated as maximization of the likelihood function of the corresponding mixture model. For the solution of the optimization problem, Bare Bones Particle Swarm Optimization (BBPSO) algorithm is applied. Illustrative example for a case study using censored data are provided in order to show the suitability of the BBPSO algorithm for this kind of problem very common in lifetime modelling.