interpolation

I've found some methods to enlarge an image but there is no solution to shrink an image. I'm currently using the nearest neighbor method. How could I do this with bilinear interpolation without using the imresize function in MATLAB? In your comments, you mentioned you wanted to resize an image using bilinear interpolation. Bear in mind that the bilinear interpolation algorithm is size independent. You can very well use the same algorithm for enlarging an image as well as shrinking an image. The right scale factors to sample the pixel locations are dependent on the output dimensions you specify

I have 2 rotation matrices (lets call them A and B) where: A = 1 0 0 0 0 -1 0 1 0 and B = -1 0 0 0 0 -1 0 -1 0 This is basically just a rotation where the camera spins around to look behind itself. Obviously I can't just interpolate the values in the matrices directly because it looks weird. I have tried converting the matrices to Euler angles which yields 2 sets of X,Y,Z angles and trying to determine which angles to use based on the minimum distance between each component of the X,Y,Z angle. That definitely results in the kind of rotation I want but I can't think of a decent way to determine

I am trying to rotate an image with Matlab without using imrotate function. I actually made it by using transformation matrix.But it is not good enough.The problem is, the rotated image is "sliding".Let me tell you with pictures. This is my image which I want to rotate: But when I rotate it ,for example 45 degrees, it becomes this: I am asking why this is happening.Here is my code,is there any mathematical or programming mistakes about it? image=torso; %image padding [Rows, Cols] = size(image); Diagonal = sqrt(Rows^2 + Cols^2); RowPad = ceil(Diagonal - Rows) + 2; ColPad = ceil(Diagonal - Cols)

The Question: What is the best way to calculate inverse distance weighted (IDW) interpolation in Python, for point locations? Some Background: Currently I'm using RPy2 to interface with R and its gstat module. Unfortunately, the gstat module conflicts with arcgisscripting which I got around by running RPy2 based analysis in a separate process. Even if this issue is resolved in a recent/future release, and efficiency can be improved, I'd still like to remove my dependency on installing R. The gstat website does provide a stand alone executable, which is easier to package with my python script,