Archive for June 2009

Wavelet-regularized image deconvolution

A Fast Thresholded Landweber Algorithm for Wavelet-Regularized Multidimensional Deconvolution
Vonesch and Unser (2008)
IEEE Trans. Image Proc. vol. 17(4), pp. 539-549

Quoting the authors, I also like to say that the recovery of the original image from the observed is an ill-posed problem. They traced the efforts of wavelet regularization in deconvolution back to a few relatively recent publications by astronomers. Therefore, I guess the topic and algorithm of this paper could drag some attentions from astronomers. Continue reading ‘Wavelet-regularized image deconvolution’ »

how to trace?

I was at the SUSY 09 public lecture given by a Nobel laureate, Frank Wilczek of QCD (quantum chromodynamics). As far as I know SUSY is the abbreviation of SUperSYmetricity in particle physics. Finding such antimatter(? I’m afraid I read “Angels and Demons” too quickly) will explain the unification theory among electromagnetic, weak, and strong forces and even the gravitation according to the speaker’s graph. I’ll not go into the details of particle physics and the standard model. The reason is too obvious. :) Instead, I’d like to show this image from wikipedia and to discuss my related questions.
particle_trace Continue reading ‘how to trace?’ »

[MADS] Adaptive filter

Please, do not confuse adaptive filter (hereafter, AF) with adaptive optics (hereafter, AO). I have no expertise in both fields but have small experiences to tell you the difference. Simply put, AF is comparable to software as opposed to AO to hardware, which is for constructing telescopes in order to collect data with sharpness and to minimize time varying atmospheric blurring. When you search adaptive filter in ADS you’ll more likely come across with adaptive optics and notch filter. Continue reading ‘[MADS] Adaptive filter’ »

Curious Cases of the Null Hypothesis Probability

Even though I traced the astronomers’ casual usage of the null hypothesis probability in a fashion of reporting outputs from data analysis packages of their choice, there were still some curious cases of the null hypothesis probability that I couldn’t solve. They are quite mysterious to me. Sometimes too much creativity harms the original intention. Here are some examples. Continue reading ‘Curious Cases of the Null Hypothesis Probability’ »

[MADS] data depth

How would you assign orders to multivariate data? If you have your strategy to achieve this ordering task, I’d like to ask, “is your strategy affine invariant?” meaning that shift and rotation invariant. Continue reading ‘[MADS] data depth’ »