On Mar 10, 2009, at 8:56 AM, Nicolas Robidoux wrote: > > Hello Rahul: > >> i m a student and interested in gsoc project:Fast Adaptive Resampler >> Tailored For Transformations Which Mostly Downsample > >> I have read the requirements properly for this project which also >> includes jacobian transformation,box filtering algorithm and >> bilinear resampling.But i am having some problem in relating all >> these in one algorithm. Please guide me.Also I would like to know >> the status of this project progress. > > The >>programming<< for this project has not started. "No progress" is > consequently a fair description. > > Computing jacobian information (for an arbitrary point transformation) > approximately using finite differences is probably too ambitious. My > current opinion is that this method should only be used when the point > transformation "communicates" this information to the sampler. ... Numerical Jacobian calculation is not so bad in terms of coding effort -- you can use the method I implemented for PDL::Transform (available as part of the PDL package for Perl, or at pdl.perl.org), and it's straightforward to code. The PDL::Transform resampling code switches its sampling technique based on user input; Jacobian based spatially variable filters are used where artifact avoidance is most important. It might make a nice starting point for you to look at. On the other hand, you will need to think a bit about the "Fast" part, which the PDL Jacobian-driven sampling is not -- mostly because of the need to supply input and output filtering. I did that by padding the singular values of the Jacobian to approximate the effect of convolving one-pixel-wide input and output filter kernels with the calculated sampling kernel. That requires subjecting a matrix to singular value decomposition for every pixel - there is almost certainly a faster way to do it. For linear transformations (where the Jacobian is constant) the method is much faster. Dodgson is a great reference (in Nicolas' email). You might also like to read Ken Turkowski's nice overview of resampling theory: http://www.worldserver.com/turk/computergraphics/ResamplingFilters.pdf My own paper on the subject (in the context of image resampling for scientific applications) is here: http://adsabs.harvard.edu/abs/2004SoPh..219....3D > > > You need to understand exact area methods, and in particular, exact > area box filtering (basically, you understand images as being a > piecewise constant surface, with the pieces determined by the set of > points which are closer to a pixel center than any other pixel center, > and you (approximately) integrate this surface over an area associated > with the new pixel centers (determined by the point transformation). > > References which may help understand what is going on are > > @TechReport{Dodgson, > author = {N. A. Dodgson}, > title = {Image resampling}, > institution = {University of Cambridge Computer Lab.}, > year = 1992, > number = {UCAM--CL--TR--261}, > address = {15 JJ Thomson Avenue, Cambridge CB3 0FD, UK}, > month = {Aug.} > } > > and > > @inproceedings{DBLP:conf/iciar/RobidouxTGT08, > author = {Nicolas Robidoux and > Adam Turcotte and > Minglun Gong and > Annie Tousignant}, > title = {Fast Exact Area Image Upsampling with Natural > Biquadratic > Histosplines}, > pages = {85-96}, > ee = {http://dx.doi.org/10.1007/978-3-540-69812-8_9}, > bibsource = {DBLP, http://dblp.uni-trier.de}, > crossref = {DBLP:conf/iciar/2008} > } > > Also, a student and I programmed a C filter (for 8-bit ppm/pgm) which > does exact area box filtering in the very simple case of pure image > resizing. If you're still interested, we'll put this on the web. > > The proposed method is none of the above. More precisely, it is a > composite method: It "fits" a new fast but accurate downsampling > method (related to box filtering) and bilinear together so that > Frankenstein is flexible and "smoothly varying." > > Note: French is my mother tongue. If you are more comfortable in > French, you can communicate with me---not this list---in > French. Obviously, English is fine too. > > Best of luck, > > Nicolas Robidoux > Universite Laurentienne > > > _______________________________________________ > Gimp-developer mailing list > Gimp-developer@xxxxxxxxxxxxxxxxxxxxxx > https://lists.XCF.Berkeley.EDU/mailman/listinfo/gimp-developer > _______________________________________________ Gimp-developer mailing list Gimp-developer@xxxxxxxxxxxxxxxxxxxxxx https://lists.XCF.Berkeley.EDU/mailman/listinfo/gimp-developer
