image processing Upsacale an Array

[younes_hajjar]

hello everyone,

I have been trying for a week to develop the Laplacian pyramid and gaussian pyramid in Labview. I have built the pyramid but unfortunately the results I was dissatisfied with it.
I think the problem is that I have written the functions : 

(DownSampling function like this:

By default, size of the output image is computed as Size((src.cols+1)/2, (src.rows+1)/2), but in any case, the following conditions should be satisfied:

|dstsize.width∗2−src.cols|≤2|dstsize.height∗2−src.rows|≤2
The function performs the downsampling step of the Gaussian pyramid construction. First, it convolves the source image with the kernel:

1/256 * [1 4 6 4 1 ; 4 16 24 16 4 ; 6 24 36 24 6 ; 4 16 24 16 4 ; 1 4 6 4 1 ] )

 and the UpSampling function like this:  he function performs the upsampling step of the Gaussian pyramid construction, though it can actually be used to construct the Laplacian pyramid. First, it upsamples the source image by injecting even zero rows and columns and then convolves the result with the same kernel as in pyrDown multiplied by 4.

now i noticed that, the UpSampling function must be written in a different syntax . in a method ( called resize: so called that in python).
does anyone know how i can get this notation(algorithm) ?

is there any function in LabView that supports this (imresize function : so called that in matlab ) ?
resize and imresize are the same

thanks for any suggestion

[altenbach]

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@younes_hajjar wrote:

I have been trying for a week to develop the Laplacian pyramid and gaussian pyramid in Labview. I have built the pyramid but unfortunately the results I was dissatisfied with it.

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A result is either correct or wrong. ("Satisfaction" only comes into play of execution speed and such matters).

Once you show us what you have (A VI or VIs, including typical example data and expected results) and point us to a link describing the math, we can probably point you in the right direction.

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@younes_hajjar wrote:

By default, size of the output image is computed as Size((src.cols+1)/2, (src.rows+1)/2), but in any case, the following conditions should be satisfied:

|dstsize.width∗2−src.cols|≤2|dstsize.height∗2−src.rows|≤2
The function performs the downsampling step of the Gaussian pyramid construction. First, it convolves the source image with the kernel:

1/256 * [1 4 6 4 1 ; 4 16 24 16 4 ; 6 24 36 24 6 ; 4 16 24 16 4 ; 1 4 6 4 1 ] )

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So this is just a convolution with a 5x5 2D gaussian. Can you explain the rest of your sparse description syntax. You talk about up-sampling AND down-sampling and it is not clear what should happen in what order. Are the original dimensions even or odd?