 Scalar Data Assignment: Isocontour vs Image Scaling - Printable Version +- CS-5630/6630 | Visualization | Fall 2014 (http://www.eng.utah.edu/~abigelow/bulletinBoard) +-- Forum: CS-5630/6630 | Visualization | Fall 2014 (/forumdisplay.php?fid=1) +--- Forum: General Discussion (/forumdisplay.php?fid=2) +--- Thread: Scalar Data Assignment: Isocontour vs Image Scaling (/showthread.php?tid=84) Scalar Data Assignment: Isocontour vs Image Scaling - accidental_PhD - 11-11-2014 11:50 AM In case others have the same question, I'm posting this email here: Quote:I have some questions about the assignment. In the 'interpolating the grid' part, we are asked to make the image larger. What I do is using nearest neighbor scaling. Is my understanding correct? In the 'isocontours using marching squares' part, the assignment says 'you should still keep your display of a fixed height of 800 pixels. However, you should isocontour on the original data and then scale up the position of the isocontours appropriately. This is not equivalent to isocontouring the bilinearly interpolated data!' What does it mean? My understanding is, firstly, we do the isocontours using the original data without making larger, which is 517*374. Then scale up the image with isocontours. When we scale up it, using bilinearly interpolating or just simple scaling up? The last question is, we are asked 'add an image of the test data set at the same isovalue as in FIGURE 5', my confusion is : is figure 5 the result of doing bilinearly interpolating after isocontours? Thank you very much! Yes, you are correct that you should first calculate the isocontours on the original, unscaled data. You can then simply scale the isocontour coordinates to the target image size, and then draw lines using those coordinates. Figure 5 is an example of this; the grey intensities in the background come from bilinear interpolation, but the isocontour overlay uses coordinates based on the original dataset (hence the straight lines - they would be smooth if you calculated the isocontours based on the scaled, interpolated data).