From 2c0b722536a4ec2f723c289b695b983741c678f8 Mon Sep 17 00:00:00 2001 From: Hans-Christoph Steiner Date: Fri, 2 Nov 2012 14:25:59 +0000 Subject: commit windows binaries from old rsync auto-build setup, including Gem 0.93.1 svn path=/trunk/; revision=16520 --- packages/noncvs/windows/extra/Gem/cMatrix.html | 270 +++++++++++++++++++++++++ 1 file changed, 270 insertions(+) create mode 100644 packages/noncvs/windows/extra/Gem/cMatrix.html (limited to 'packages/noncvs/windows/extra/Gem/cMatrix.html') diff --git a/packages/noncvs/windows/extra/Gem/cMatrix.html b/packages/noncvs/windows/extra/Gem/cMatrix.html new file mode 100644 index 00000000..fe4cd044 --- /dev/null +++ b/packages/noncvs/windows/extra/Gem/cMatrix.html @@ -0,0 +1,270 @@ + + +Matrix Operations for Image Processing + + +
+

Matrix Operations for Image Processing

+

Paul Haeberli

+

Nov 1993

+Horiz Bar +

Introduction

+

+Four by four matrices are commonly used to transform geometry for 3D +rendering. These matrices may also be used to transform RGB colors, to scale +RGB colors, and to control hue, saturation and contrast. The most important +advantage of using matrices is that any number of color transformations +can be composed using standard matrix multiplication. +

+Please note that for these operations to be correct, we really must operate +on linear brightness values. If the input image is in a non-linear brightness +space RGB colors must be transformed into a linear space before these +matrix operations are used. + +

Color Transformation

+RGB colors are transformed by a four by four matrix as shown here: + +
+    xformrgb(mat,r,g,b,tr,tg,tb)
+    float mat[4][4];
+    float r,g,b;
+    float *tr,*tg,*tb;
+    {
+        *tr = r*mat[0][0] + g*mat[1][0] +
+		    b*mat[2][0] + mat[3][0];
+        *tg = r*mat[0][1] + g*mat[1][1] +
+		    b*mat[2][1] + mat[3][1];
+        *tb = r*mat[0][2] + g*mat[1][2] +
+		    b*mat[2][2] + mat[3][2];
+    }
+
+ +

The Identity

+This is the identity matrix: +
+    float mat[4][4] = {
+        1.0,    0.0,    0.0,    0.0,
+        0.0,    1.0,    0.0,    0.0,
+        0.0,    0.0,    1.0,    0.0,
+        0.0,    0.0,    0.0,    1.0,
+    };
+
+Transforming colors by the identity matrix will leave them unchanged. + +

Changing Brightness

+To scale RGB colors a matrix like this is used: +
+    float mat[4][4] = {
+        rscale, 0.0,    0.0,    0.0,
+        0.0,    gscale, 0.0,    0.0,
+        0.0,    0.0,    bscale, 0.0,
+        0.0,    0.0,    0.0,    1.0,
+    };
+
+Where rscale, gscale, and bscale specify how much to scale the r, g, and b +components of colors. This can be used to alter the color balance of an image. +

+In effect, this calculates: +

+	tr = r*rscale;
+	tg = g*gscale;
+	tb = b*bscale;
+
+ +

Modifying Saturation

+ + +

Converting to Luminance

+To convert a color image into a black and white image, this matrix is used: +
+    float mat[4][4] = {
+        rwgt,   rwgt,   rwgt,   0.0,
+        gwgt,   gwgt,   gwgt,   0.0,
+        bwgt,   bwgt,   bwgt,   0.0,
+        0.0,    0.0,    0.0,    1.0,
+    };
+
+Where rwgt is 0.3086, gwgt is 0.6094, and bwgt is 0.0820. This is the +luminance vector. Notice here that we do not use the standard NTSC weights +of 0.299, 0.587, and 0.114. The NTSC weights are only applicable to RGB +colors in a gamma 2.2 color space. For linear RGB colors the values above +are better. +

+In effect, this calculates: +

+	tr = r*rwgt + g*gwgt + b*bwgt;
+	tg = r*rwgt + g*gwgt + b*bwgt;
+	tb = r*rwgt + g*gwgt + b*bwgt;
+
+ +

Modifying Saturation

+ +To saturate RGB colors, this matrix is used: + +
+     float mat[4][4] = {
+        a,      b,      c,      0.0,
+        d,      e,      f,      0.0,
+        g,      h,      i,      0.0,
+        0.0,    0.0,    0.0,    1.0,
+    };
+
+Where the constants are derived from the saturation value s +as shown below: + +
+    a = (1.0-s)*rwgt + s;
+    b = (1.0-s)*rwgt;
+    c = (1.0-s)*rwgt;
+    d = (1.0-s)*gwgt;
+    e = (1.0-s)*gwgt + s;
+    f = (1.0-s)*gwgt;
+    g = (1.0-s)*bwgt;
+    h = (1.0-s)*bwgt;
+    i = (1.0-s)*bwgt + s;
+
+One nice property of this saturation matrix is that the luminance +of input RGB colors is maintained. This matrix can also be used +to complement the colors in an image by specifying a saturation +value of -1.0. +

+Notice that when s is set to 0.0, the matrix is exactly +the "convert to luminance" matrix described above. When s +is set to 1.0 the matrix becomes the identity. All saturation matrices +can be derived by interpolating between or extrapolating beyond these +two matrices. +

+This is discussed in more detail in the note on +Image Processing By Interpolation and Extrapolation. +

Applying Offsets to Color Components

+To offset the r, g, and b components of colors in an image this matrix is used: +
+    float mat[4][4] = {
+        1.0,    0.0,    0.0,    0.0,
+        0.0,    1.0,    0.0,    0.0,
+        0.0,    0.0,    1.0,    0.0,
+        roffset,goffset,boffset,1.0,
+    };
+
+This can be used along with color scaling to alter the contrast of RGB +images. + +

Simple Hue Rotation

+To rotate the hue, we perform a 3D rotation of RGB colors about the diagonal +vector [1.0 1.0 1.0]. The transformation matrix is derived as shown here: +

+ If we have functions:

+

+
identmat(mat) +
that creates an identity matrix. +
+
+
xrotatemat(mat,rsin,rcos) +
that multiplies a matrix that rotates about the x (red) axis. +
+
+
yrotatemat(mat,rsin,rcos) +
that multiplies a matrix that rotates about the y (green) axis. +
+
+
zrotatemat(mat,rsin,rcos) +
that multiplies a matrix that rotates about the z (blue) axis. +
+Then a matrix that rotates about the 1.0,1.0,1.0 diagonal can be +constructed like this: +
+First we make an identity matrix +
+    identmat(mat);
+
+Rotate the grey vector into positive Z +
+    mag = sqrt(2.0);
+    xrs = 1.0/mag;
+    xrc = 1.0/mag;
+    xrotatemat(mat,xrs,xrc);
+
+    mag = sqrt(3.0);
+    yrs = -1.0/mag;
+    yrc = sqrt(2.0)/mag;
+    yrotatemat(mat,yrs,yrc);
+
+Rotate the hue +
+    zrs = sin(rot*PI/180.0);
+    zrc = cos(rot*PI/180.0);
+    zrotatemat(mat,zrs,zrc);
+
+Rotate the grey vector back into place +
+    yrotatemat(mat,-yrs,yrc);
+    xrotatemat(mat,-xrs,xrc);
+
+The resulting matrix will rotate the hue of the input RGB colors. A rotation +of 120.0 degrees will exactly map Red into Green, Green into Blue and +Blue into Red. This transformation has one problem, however, the luminance +of the input colors is not preserved. This can be fixed with the following +refinement: + +

Hue Rotation While Preserving Luminance

+ +We make an identity matrix +
+   identmat(mmat);
+
+Rotate the grey vector into positive Z +
+    mag = sqrt(2.0);
+    xrs = 1.0/mag;
+    xrc = 1.0/mag;
+    xrotatemat(mmat,xrs,xrc);
+    mag = sqrt(3.0);
+    yrs = -1.0/mag;
+    yrc = sqrt(2.0)/mag;
+    yrotatemat(mmat,yrs,yrc);
+    matrixmult(mmat,mat,mat);
+
+Shear the space to make the luminance plane horizontal +
+    xformrgb(mmat,rwgt,gwgt,bwgt,&lx,&ly,&lz);
+    zsx = lx/lz;
+    zsy = ly/lz;
+    zshearmat(mat,zsx,zsy);
+
+Rotate the hue +
+    zrs = sin(rot*PI/180.0);
+    zrc = cos(rot*PI/180.0);
+    zrotatemat(mat,zrs,zrc);
+
+Unshear the space to put the luminance plane back +
+    zshearmat(mat,-zsx,-zsy);
+
+Rotate the grey vector back into place +
+    yrotatemat(mat,-yrs,yrc);
+    xrotatemat(mat,-xrs,xrc);
+
+

Conclusion

+I've presented several matrix transformations that may be applied +to RGB colors. Each color transformation is represented by +a 4 by 4 matrix, similar to matrices commonly used to transform 3D geometry. +

+Example C code +that demonstrates these concepts is provided for your enjoyment. +

+These transformations allow us to adjust image contrast, brightness, hue and +saturation individually. In addition, color matrix transformations concatenate +in a way similar to geometric transformations. Any sequence of +operations can be combined into a single matrix using +matrix multiplication. +

+

+ +
+
+
+ + + -- cgit v1.2.1