KinectDepthSmoothingBin.zip
KinectDepthSmoothing.exe
KinectDepthSmoothingBin3.zip
KinectDepthSmoothing.exe
KinectDepthSmoothingSrc.zip
KinectDepthSmoothing
Properties
Settings.settings
KinectDepthSmoothingSrc3.zip
Settings.settings
KinectDepthSmoothing_bin_.zip
KinectDepthSmoothing.exe
KinectDepthSmoothing_src_.zip
Settings.settings

using System.Threading.Tasks;
using System.Windows;
using System.Collections.Generic;
namespace KinectDepthSmoothing
{
public partial class MainWindow : Window
{
private short[] CreateFilteredDepthArray(short[] depthArray, int width, int height)
{
/////////////////////////////////////////////////////////////////////////////////////
// I will try to comment this as well as I can in here, but you should probably refer
// to my Code Project article for a more in depth description of the method.
/////////////////////////////////////////////////////////////////////////////////////
short[] smoothDepthArray = new short[depthArray.Length];
// We will be using these numbers for constraints on indexes
int widthBound = width  1;
int heightBound = height  1;
// We process each row in parallel
Parallel.For(0, 240, depthArrayRowIndex =>
{
// Process each pixel in the row
for (int depthArrayColumnIndex = 0; depthArrayColumnIndex < 320; depthArrayColumnIndex++)
{
var depthIndex = depthArrayColumnIndex + (depthArrayRowIndex * 320);
// We are only concerned with eliminating 'white' noise from the data.
// We consider any pixel with a depth of 0 as a possible candidate for filtering.
if (depthArray[depthIndex] == 0)
{
// From the depth index, we can determine the X and Y coordinates that the index
// will appear in the image. We use this to help us define our filter matrix.
int x = depthIndex % 320;
int y = (depthIndex  x) / 320;
// The filter collection is used to count the frequency of each
// depth value in the filter array. This is used later to determine
// the statistical mode for possible assignment to the candidate.
short[,] filterCollection = new short[24,2];
// The inner and outer band counts are used later to compare against the threshold
// values set in the UI to identify a positive filter result.
int innerBandCount = 0;
int outerBandCount = 0;
// The following loops will loop through a 5 X 5 matrix of pixels surrounding the
// candidate pixel. This defines 2 distinct 'bands' around the candidate pixel.
// If any of the pixels in this matrix are non0, we will accumulate them and count
// how many non0 pixels are in each band. If the number of non0 pixels breaks the
// threshold in either band, then the average of all non0 pixels in the matrix is applied
// to the candidate pixel.
for (int yi = 2; yi < 3; yi++)
{
for (int xi = 2; xi < 3; xi++)
{
// yi and xi are modifiers that will be subtracted from and added to the
// candidate pixel's x and y coordinates that we calculated earlier. From the
// resulting coordinates, we can calculate the index to be addressed for processing.
// We do not want to consider the candidate pixel (xi = 0, yi = 0) in our process at this point.
// We already know that it's 0
if (xi != 0  yi != 0)
{
// We then create our modified coordinates for each pass
var xSearch = x + xi;
var ySearch = y + yi;
// While the modified coordinates may in fact calculate out to an actual index, it
// might not be the one we want. Be sure to check to make sure that the modified coordinates
// match up with our image bounds.
if (xSearch >= 0 && xSearch <= widthBound && ySearch >= 0 && ySearch <= heightBound)
{
var index = xSearch + (ySearch * width);
// We only want to look for non0 values
if (depthArray[index] != 0)
{
// We want to find count the frequency of each depth
for (int i = 0; i < 24; i++)
{
if (filterCollection[i, 0] == depthArray[index])
{
// When the depth is already in the filter collection
// we will just increment the frequency.
filterCollection[i, 1]++;
break;
}
else if (filterCollection[i, 0] == 0)
{
// When we encounter a 0 depth in the filter collection
// this means we have reached the end of values already counted.
// We will then add the new depth and start it's frequency at 1.
filterCollection[i, 0] = depthArray[index];
filterCollection[i, 1]++;
break;
}
}
// We will then determine which band the non0 pixel
// was found in, and increment the band counters.
if (yi != 2 && yi != 2 && xi != 2 && xi != 2)
innerBandCount++;
else
outerBandCount++;
}
}
}
}
}
// Once we have determined our inner and outer band nonzero counts, and accumulated all of those values,
// we can compare it against the threshold to determine if our candidate pixel will be changed to the
// statistical mode of the nonzero surrounding pixels.
if (innerBandCount >= innerBandThreshold  outerBandCount >= outerBandThreshold)
{
short frequency = 0;
short depth = 0;
// This loop will determine the statistical mode
// of the surrounding pixels for assignment to
// the candidate.
for (int i = 0; i < 24; i++)
{
// This means we have reached the end of our
// frequency distribution and can break out of the
// loop to save time.
if (filterCollection[i,0] == 0)
break;
if (filterCollection[i, 1] > frequency)
{
depth = filterCollection[i, 0];
frequency = filterCollection[i, 1];
}
}
smoothDepthArray[depthIndex] = depth;
}
}
else
{
// If the pixel is not zero, we will keep the original depth.
smoothDepthArray[depthIndex] = depthArray[depthIndex];
}
}
});
return smoothDepthArray;
}
}
}

By viewing downloads associated with this article you agree to the Terms of Service and the article's licence.
If a file you wish to view isn't highlighted, and is a text file (not binary), please
let us know and we'll add colourisation support for it.
Karl Sanford
Software Developer
Open Systems Technologies
United States
First learned to program in 1997 on my TI83 and have been doing it ever since, with a foray into networking and infrastructure.
Mostly a C# junky (Win\Web Forms, WP7.5/8, WPF and MVC), though I have experience with many other technologies and products.
I have also been trying to learn and apply more in the area of AI; focusing on computer vision, natural language processing, and classification.
In my spare time, I love to tinker with electronics and various useless DIY projects.
My brain is a shark... if it stops moving, it will die. I'm always looking to learn more.