Yes, just be aware that MATLAB’s imresize has anti-aliasing enabled by default: imresize(A,scale,’bilinear’) vs. what you would get with cv::resize(), which does not have anti-aliasing: imresize(A,scale,’bilinear’,’AntiAliasing’,false) And as Amro mentioned, the default in MATLAB is bicubic, so be sure to specify. Bilinear No code modifications are necessary to get matching results with bilinear interpolation. Example … Read more
Looks like you got it. In your upper code example and in your previous (linked) question you have structured data. Which can be interpolated using RectBivariateSpline or interp2d. This means you have data that can be described on a grid (all points on the grid have a known value). The grid doesn’t necessarily have to … Read more
This should work – just linearly scale the red and green values. Assuming your max red/green/blue value is 255, and n is in range 0 .. 100 R = (255 * n) / 100 G = (255 * (100 – n)) / 100 B = 0 (Amended for integer maths, tip of the hat to … Read more
Cubic b-spline has been recently descried in a series of papers by Unser, Thévenaz et al., see among others M. Unser, A. Aldroubi, M. Eden, “Fast B-Spline Transforms for Continuous Image Representation and Interpolation”, IEEE Trans. Pattern Anal. Machine Intell., vol. 13, n. 3, pp. 277-285, Mar. 1991. M. Unser, “Splines, a Perfect Fit for … Read more
So if your control points are always on the same x coordinate and linearly dispersed along whole range then you can do it like this: //————————————————————————— const int N=5; // number of control points (must be >= 4) float ctrl[N]= // control points y values initiated with linear function y=x { // x value is … Read more
Recently I ran across the same question and wanted to implemented it on my own. This image from Wikipedia helped me: The following code is written in C++ and shows how to compute a quadratic bezier. int getPt( int n1 , int n2 , float perc ) { int diff = n2 – n1; return … Read more
I would use this interpolation cubic: x=a0+a1*t+a2*t*t+a3*t*t*t y=b0+b1*t+b2*t*t+b3*t*t*t where a0..a3 are computed like this: d1=0.5*(p2.x-p0.x); d2=0.5*(p3.x-p1.x); a0=p1.x; a1=d1; a2=(3.0*(p2.x-p1.x))-(2.0*d1)-d2; a3=d1+d2+(2.0*(-p2.x+p1.x)); b0 .. b3 are computed in same way but use y coordinates of course p0..p3 are control points for cubic interpolation curve t = < 0.0 , 1.0 > is curve parameter from p1 to … Read more
In MATLAB you can use either the function griddata or the TriScatteredInterp class (Note: as of R2013a scatteredInterpolant is the recommended alternative). Both of these allow you to fit a surface of regularly-spaced data to a set of nonuniformly-spaced points (although it appears griddata is no longer recommended in newer MATLAB versions). Here’s how you … Read more
An alternative to @tasseKATT’s answer (which doesn’t require a controller function) is to use string concatenation directly in the expression a filter: angular.module(‘myApp’) .filter(‘youtubeEmbedUrl’, function ($sce) { return function(videoId) { return $sce.trustAsResourceUrl(‘http://www.youtube.com/embed/’ + videoId); }; }); <div ng-src=”https://stackoverflow.com/questions/23405162/{{ video.id.videoId” youtubeEmbedUrl }}”></div> I’ve found this particularly useful when using SVG icon sprites, which requires you to … Read more
What you want is called planar rectification, and it’s not all that simple, I’m afraid. What you need to do is recover the homography that maps this oblique view of the van side onto the front-facing view. Photoshop / etc. have tools to do this for you given some control points; if you want to … Read more