… , sampling density correction is … on sampling density correction. The error from the gridding
step has been characterized and minimized for even modest oversampling ratios and kernel …

… In summary, we implement a fast and efficient geometric correction technique [7] and use …
of the surface geometry is leveraged to densely measure defocus kernels near regions where …

… lar samples, the most severely non-zero intercept of the basic kernel estimate results in linear
correction erro… Finally in this section, we display a few linearly corrected boundary kernels …

… setting where samples are obtained via the … sampling yields consistent estimators for
quantities related to a target distribution of interest by using samples obtained from a geometrically …

… out the geometric correction of slant images with the folded spectrum. On the other hand,
under-sampling may happen in the geometric correction, … The new 2D sinc interpolation kernel …

… Points distributions are generated by sampling this model. This new formulation of the … We
derive a highly efficient multi-scale sampling scheme for drawing random point distributions …

… We introduce a simple geometric method for removing edge effects from kernel-type nonpar~…
The usual kernel-type estimator may be applied to the new, enlarged data set, Without any …

… here but at larger numbers of samples that we have examined. The higher-order kernels
do reduce bias compared to the KDE, but higher-order kernel estimators have larger IMSE's …

… , we identify fundamental geometric structures that underlie the problems of sampling, …
geometric structures to solve these problems efficiently. We show that a wide range of geometric …

… to extract the watermark by classifying samples derived from watermarked image. Yang
et al. [17] presented a geometric correction based robust color image watermarking scheme …