The spatial resolution of astronomical images is limited by atmospheric turbulence and diffraction in the telescope optics, resulting blurred images. This makes it difficult to accurately measure brightness blended objects because contributions from adjacent are mixed a time-variable manner due changes conditions. However, this effect can be corrected characterizing Point Spread Function (PSF),...

Synthetic aperture imaging radiometers (SAIRs) are powerful passive microwave systems for high-resolution by use of synthetic technique. However, the ill-posed inverse problem SAIRs makes it difficult to reconstruct high-precision brightness temperature map. The traditional regularization methods add a unique penalty all frequency bands solution, which may cause reconstructed result be too smoo...

We consider the local regularization problem for integral equations of the first kind, generalizing previous work which applied only to problems of Volterra type. Our approach allows for local control of the regularization process, allowing for resolution of fine/sharp features of solutions without having to resort to nondifferentiable optimization techniques. In addition we present examples il...

Harmonic surface deformation is a well-known geometric modeling method that creates plausible deformations in an interactive manner. However, this method is susceptible to artifacts, in particular close to the deformation handles. These artifacts often correlate with strong gradients of the deformation energy. In this work, we propose a novel formulation of harmonic surface deformation, which i...

Tikhonov regularization is one of the most popular methods for the solution of linear discrete ill-posed problems. In many applications the desired solution is known to lie in the nonnegative cone. It is then natural to require that the approximate solution determined by Tikhonov regularization also lies in this cone. The present paper describes two iterative methods, that employ modulus-based ...

Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2 < q < 1) regularizations, to select key risk factors in the Cox's proportional hazards model using microarray gene expression data...

Current methods for computing vortex sheet separation use a regularization parameter which is discontinuous from the body to the vortex sheet. We propose two methods for reducing the errors associated with the discontinuity and improving convergence with respect to the regularization parameter. The ‘‘velocity smoothing” method is the simpler of the two, and removes the discontinuity in regulari...