English Metric Units and Open XML

Emu
[image by blmurch]

In this article, you’ll find out how English Metric Units (or EMUs) are related to the Open XML format. So what are English Metric Units? They are … actually, I have no idea what they are. Here’s the best answer I could find on EMUs. And there’s the Open XML explanation on EMUs in Wikipedia.

I stumbled upon EMUs because I was trying to create an Excel spreadsheet using the Open XML format. The task require the addition of an image in one of the Excel sheets. You have no idea how much code I needed to write just to include one image. (I’ll tell you about that in another article. Let’s focus on EMUs here.)

Basically, there’s no unifying unit, no “one ring to bind them all”: centimetres, inches and points. So they used a new unit of measurement to represent the dimensions of an image. *sigh*

Anyway, while searching for how to convert pixels to EMUs, I stumbled upon 2 articles on StackOverflow: Pixel to Centimetre and Pixel to Point.

From the Wikipedia article, there are 914400 EMUs per inch, and there are 96 pixels to an inch. Therefore, I figured the pixel to EMU formula is

EMU = pixel * 914400 / 96

There’s a flaw, in that the dots per inch (DPI) may be different for different monitors. For example, there could be 72 pixels in an inch. The best I could do is to assume that, the image created with one monitor, will be used on another monitor with the same DPI. Thus:

EMU = pixel * 914400 / Resolution

Here’s some code to visualise that:

Bitmap bm = new Bitmap("yourimage.jpg");
DocumentFormat.OpenXml.Drawing.Extents extents = new DocumentFormat.OpenXml.Drawing.Extents();
extents.Cx = (long)bm.Width * (long)((float)914400 / bm.HorizontalResolution);
extents.Cy = (long)bm.Height * (long)((float)914400 / bm.VerticalResolution);

There, now you know how English Metric Units are related to Open XML formats.

There’s updated material and source code, together with more information on how to work with Open XML. Click here to find out more.

P.S. English Metric Units have no relation to emus. Other than their (unfortunate?) acronym being exactly the same as the name of the Dromaius novaehollandiae

Image rotation with bilinear interpolation

In this article, I’ll show you how to rotate an image about its centre. 3 assignment methods will be shown,

  • assign source pixels to destination pixels
  • assign destination pixels from source pixels
  • assign destination pixels from source pixels with bilinear interpolation

I’ll show you the code, then the results for comparison. So what’s bilinear interpolation?

Bilinear interpolation

Read up on linear interpolation first if you haven’t done so. “Bilinear” means there are 2 directions to interpolate. Let me illustrate.

Bilinear interpolation

In our case, we’re interpolating between 4 pixels. Visualise each pixel as a single point. Linearly interpolate between the top 2 pixels. Linearly interpolate between the bottom 2 pixels. Then linearly interpolate between the calculated results of the previous two.

You can expand on this concept to get trilinear interpolation.

Trilinear interpolation

LERPs is a short form of linear interpolations. When would trilinear interpolation be useful? Voxels, which is out of scope in this article.

Defining the centre of an image

I’m going to be fuzzy about this. I’m going to just take one pixel in the image and define it as the centre. This pixel is defined as having a horizontal index equal to half of its width (rounded down), and a vertical index equal to half its height (rounded down).

This means the image isn’t rotated about its “true” centre, but with a relatively large size, it won’t matter anyway. It’s not like you’re rotating an image of 5 pixel width and 3 pixel height, right?

The preparation part

The actual code is quite long, so I’m separating it into 4 parts.

  • Initialisation and variable declaration
  • Assigning source pixels to destination pixels
  • Assigning destination pixels from source pixels
  • Assigning destination pixels from source pixels with bilinear interpolation

It’s hard-coded with -30 degrees as the angle of rotation, but you can easily write it into a function.

// 30 deg = PI/6 rad
// rotating clockwise, so it's negative relative to Cartesian quadrants
const double cnAngle = -0.52359877559829887307710723054658;
// use whatever image you fancy
Bitmap bm = new Bitmap("rotationsource.jpg");
// general iterators
int i, j;
// calculated indices in Cartesian coordinates
int x, y;
double fDistance, fPolarAngle;
// for use in neighbouring indices in Cartesian coordinates
int iFloorX, iCeilingX, iFloorY, iCeilingY;
// calculated indices in Cartesian coordinates with trailing decimals
double fTrueX, fTrueY;
// for interpolation
double fDeltaX, fDeltaY;
// pixel colours
Color clrTopLeft, clrTopRight, clrBottomLeft, clrBottomRight;
// interpolated "top" pixels
double fTopRed, fTopGreen, fTopBlue;
// interpolated "bottom" pixels
double fBottomRed, fBottomGreen, fBottomBlue;
// final interpolated colour components
int iRed, iGreen, iBlue;
int iCentreX, iCentreY;
int iWidth, iHeight;
iWidth = bm.Width;
iHeight = bm.Height;

iCentreX = iWidth / 2;
iCentreY = iHeight / 2;

Bitmap bmSourceToDestination = new Bitmap(iWidth, iHeight);
Bitmap bmDestinationFromSource = new Bitmap(iWidth, iHeight);
Bitmap bmBilinearInterpolation = new Bitmap(iWidth, iHeight);

for (i = 0; i < iHeight; ++i)
{
    for (j = 0; j < iWidth; ++j)
    {
        // initialise when "throwing" values
        bmSourceToDestination.SetPixel(j, i, Color.Black);
        // since we're looping, we might as well do for the others
        bmDestinationFromSource.SetPixel(j, i, Color.Black);
        bmBilinearInterpolation.SetPixel(j, i, Color.Black);
    }
}

Some of it might not mean anything to you yet. Just wait for the rest of the code. You might want to read up on converting between raster, Cartesian and polar coordinates first before moving on.

Throwing values from source to destination

// assigning pixels from source image to destination image
for (i = 0; i < iHeight; ++i)
{
    for (j = 0; j < iWidth; ++j)
    {
        // convert raster to Cartesian
        x = j - iCentreX;
        y = iCentreY - i;

        // convert Cartesian to polar
        fDistance = Math.Sqrt(x * x + y * y);
        fPolarAngle = 0.0;
        if (x == 0)
        {
            if (y == 0)
            {
                // centre of image, no rotation needed
                bmSourceToDestination.SetPixel(j, i, bm.GetPixel(j, i));
                continue;
            }
            else if (y < 0)
            {
                fPolarAngle = 1.5 * Math.PI;
            }
            else
            {
                fPolarAngle = 0.5 * Math.PI;
            }
        }
        else
        {
            fPolarAngle = Math.Atan2((double)y, (double)x);
        }

        // the crucial rotation part
        fPolarAngle += cnAngle;

        // convert polar to Cartesian
        x = (int)(Math.Round(fDistance * Math.Cos(fPolarAngle)));
        y = (int)(Math.Round(fDistance * Math.Sin(fPolarAngle)));

        // convert Cartesian to raster
        x = x + iCentreX;
        y = iCentreY - y;

        // check bounds
        if (x < 0 || x >= iWidth || y < 0 || y >= iHeight) continue;

        bmSourceToDestination.SetPixel(x, y, bm.GetPixel(j, i));
    }
}
bmSourceToDestination.Save("rotationsrctodest.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);

It should be fairly easy to read. Note the part about checking for the central pixel of the image. No rotation calculation necessary, so we assign and move to the next pixel. Note also the part about checking boundaries.

Finding values from the source

// assigning pixels of destination image from source image
for (i = 0; i < iHeight; ++i)
{
    for (j = 0; j < iWidth; ++j)
    {
        // convert raster to Cartesian
        x = j - iCentreX;
        y = iCentreY - i;

        // convert Cartesian to polar
        fDistance = Math.Sqrt(x * x + y * y);
        fPolarAngle = 0.0;
        if (x == 0)
        {
            if (y == 0)
            {
                // centre of image, no rotation needed
                bmDestinationFromSource.SetPixel(j, i, bm.GetPixel(j, i));
                continue;
            }
            else if (y < 0)
            {
                fPolarAngle = 1.5 * Math.PI;
            }
            else
            {
                fPolarAngle = 0.5 * Math.PI;
            }
        }
        else
        {
            fPolarAngle = Math.Atan2((double)y, (double)x);
        }

        // the crucial rotation part
        // "reverse" rotate, so minus instead of plus
        fPolarAngle -= cnAngle;

        // convert polar to Cartesian
        x = (int)(Math.Round(fDistance * Math.Cos(fPolarAngle)));
        y = (int)(Math.Round(fDistance * Math.Sin(fPolarAngle)));

        // convert Cartesian to raster
        x = x + iCentreX;
        y = iCentreY - y;

        // check bounds
        if (x < 0 || x >= iWidth || y < 0 || y >= iHeight) continue;

        bmDestinationFromSource.SetPixel(j, i, bm.GetPixel(x, y));
    }
}
bmDestinationFromSource.Save("rotationdestfromsrc.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);

The key difference here is the use of the rotation angle. Instead of adding it, we subtract it. The reason is, we rotate source pixels 30 degrees clockwise and assign it to destination pixels. But from destination pixels, we get source pixels which are rotated 30 degrees anticlockwise. Either way, we get a destination image that's the source image rotated 30 degrees clockwise.

Rotating the other way

Also compare the assignment, noting the indices:

bmSourceToDestination.SetPixel(x, y, bm.GetPixel(j, i));
bmDestinationFromSource.SetPixel(j, i, bm.GetPixel(x, y));

x and y variables are calculated and thus "messy". I prefer my messy indices on the right. There's a practical reason for it too, which will be evident when I show you the rotation results.

Image rotation code with bilinear interpolation

// assigning pixels of destination image from source image
// with bilinear interpolation
for (i = 0; i < iHeight; ++i)
{
    for (j = 0; j < iWidth; ++j)
    {
        // convert raster to Cartesian
        x = j - iCentreX;
        y = iCentreY - i;

        // convert Cartesian to polar
        fDistance = Math.Sqrt(x * x + y * y);
        fPolarAngle = 0.0;
        if (x == 0)
        {
            if (y == 0)
            {
                // centre of image, no rotation needed
                bmBilinearInterpolation.SetPixel(j, i, bm.GetPixel(j, i));
                continue;
            }
            else if (y < 0)
            {
                fPolarAngle = 1.5 * Math.PI;
            }
            else
            {
                fPolarAngle = 0.5 * Math.PI;
            }
        }
        else
        {
            fPolarAngle = Math.Atan2((double)y, (double)x);
        }

        // the crucial rotation part
        // "reverse" rotate, so minus instead of plus
        fPolarAngle -= cnAngle;

        // convert polar to Cartesian
        fTrueX = fDistance * Math.Cos(fPolarAngle);
        fTrueY = fDistance * Math.Sin(fPolarAngle);

        // convert Cartesian to raster
        fTrueX = fTrueX + (double)iCentreX;
        fTrueY = (double)iCentreY - fTrueY;

        iFloorX = (int)(Math.Floor(fTrueX));
        iFloorY = (int)(Math.Floor(fTrueY));
        iCeilingX = (int)(Math.Ceiling(fTrueX));
        iCeilingY = (int)(Math.Ceiling(fTrueY));

        // check bounds
        if (iFloorX < 0 || iCeilingX < 0 || iFloorX >= iWidth || iCeilingX >= iWidth || iFloorY < 0 || iCeilingY < 0 || iFloorY >= iHeight || iCeilingY >= iHeight) continue;

        fDeltaX = fTrueX - (double)iFloorX;
        fDeltaY = fTrueY - (double)iFloorY;

        clrTopLeft = bm.GetPixel(iFloorX, iFloorY);
        clrTopRight = bm.GetPixel(iCeilingX, iFloorY);
        clrBottomLeft = bm.GetPixel(iFloorX, iCeilingY);
        clrBottomRight = bm.GetPixel(iCeilingX, iCeilingY);

        // linearly interpolate horizontally between top neighbours
        fTopRed = (1 - fDeltaX) * clrTopLeft.R + fDeltaX * clrTopRight.R;
        fTopGreen = (1 - fDeltaX) * clrTopLeft.G + fDeltaX * clrTopRight.G;
        fTopBlue = (1 - fDeltaX) * clrTopLeft.B + fDeltaX * clrTopRight.B;

        // linearly interpolate horizontally between bottom neighbours
        fBottomRed = (1 - fDeltaX) * clrBottomLeft.R + fDeltaX * clrBottomRight.R;
        fBottomGreen = (1 - fDeltaX) * clrBottomLeft.G + fDeltaX * clrBottomRight.G;
        fBottomBlue = (1 - fDeltaX) * clrBottomLeft.B + fDeltaX * clrBottomRight.B;

        // linearly interpolate vertically between top and bottom interpolated results
        iRed = (int)(Math.Round((1 - fDeltaY) * fTopRed + fDeltaY * fBottomRed));
        iGreen = (int)(Math.Round((1 - fDeltaY) * fTopGreen + fDeltaY * fBottomGreen));
        iBlue = (int)(Math.Round((1 - fDeltaY) * fTopBlue + fDeltaY * fBottomBlue));

        // make sure colour values are valid
        if (iRed < 0) iRed = 0;
        if (iRed > 255) iRed = 255;
        if (iGreen < 0) iGreen = 0;
        if (iGreen > 255) iGreen = 255;
        if (iBlue < 0) iBlue = 0;
        if (iBlue > 255) iBlue = 255;

        bmBilinearInterpolation.SetPixel(j, i, Color.FromArgb(iRed, iGreen, iBlue));
    }
}
bmBilinearInterpolation.Save("rotationbilinearinterpolation.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);

This part is similar to the destination-from-source part, with a lot more calculations. We have to find the 4 pixels that surrounds our "true" position-calculated pixel. Then we perform linear interpolation on the 4 neighbouring pixels.

We need to interpolate for the red, green and blue components individually. Refer to my article on colour theory for a refresher.

Pictures, pictures!

After doing all that, we're finally done. Let me show you my source image first.

Rotation source

I added the marble cylinder for emphasising image quality. I needed something that's straight (vertically or horizontally) in the source image.

Here's what we get after rotating with the source-to-destination method:

Rotation - source to destination

Note the speckled black pixels dotted all over. This is because some of the destination pixels (which are within the image bounds) were unassigned.

Note also that the specks even form patterns. This is due to the sine and cosine functions, and the regularity of pixel width and height. Sine and cosine are periodic functions. Since pixel indices are regular, therefore sine and cosine results are regular too. Hence, calculations regularly fail to assign pixel values.

There might be source pixels that have the same calculated destination pixel (due to sine and cosine and rounding). This also implies that there might be anti-gravity destination pixels that no source pixel can ever matched to! I haven't verified this, but it seems a possibility.

Anti-gravity destination pixel

Still think you should iterate over the source (image/array) instead of over the destination?

Next, we have the image result of the destination-from-source method:

Rotation - destination from source

Compare the quality with the source-to-destination part. No missing pixels. It's still sort of grainy though. This is because some of the destination pixels get their values from the same source pixel, so there might be 2 side-by-side destination pixels with the same colour. This gives mini blocks of identical colour in the result, which on the whole, gives an unpolished look.

Now, we have the bilinear interpolation incorporated version.

Rotation - destination from source with bilinear interpolation

It looks smoother, right? Note the straight edge of the marble cylinder. Compare with the image result without bilinear interpolation.

I might do a version with cubic interpolation for even smoother results, but I feel the bilinear version is good enough for now. Have fun!

[UPDATE: Now, there's a version without the resulting image being clipped.]

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