2D to 3D conversion using Dubois Anaglyph algorithm - algorithm

Question

Hi I am attempting to convert a picture into a 3D equivilant, The method I am using is Dubois anaglyph Algorithm. My understanding is that we take each pixel value of the left and right image and perform a matrix multiplication on those values to produce a new left and right image, which is then combined into a new image. Is there something I am missing? Or is my understanding totally incorrect?. Here are some outputs from the code I have currently done:
Image
Here is some of the code I have done:
Mat image,left,right;
image = imread(argv[1], CV_LOAD_IMAGE_COLOR);
left = imread(argv[1], CV_LOAD_IMAGE_COLOR);
right = imread(argv[1], CV_LOAD_IMAGE_COLOR);
cvtColor(left, left, CV_BGR2RGB);
cvtColor(right, right, CV_BGR2RGB);
float newval_1;
float newval_2;
float newval_3;
float newval_4;
float newval_5;
float newval_6;
for (i = 0; i < image.rows; i++)
{
for (j = 0; j < image.cols; j++)
{
newval_1 = float(right.at<Vec3b>(i,j)[0]); // red
newval_2 = float(right.at<Vec3b>(i,j)[1]); // Green
newval_3 = float(right.at<Vec3b>(i,j)[2]); // blue
temparr[0][0]=newval_1;
temparr[0][3]=newval_2;
temparr[0][4]=newval_3;
matrixmulti(temparr,p2Right);//multiplies the current right pixel with the right matrix as in th algorithm
//Clip values <0 or >1
if(outputarr[0][0]<0){
outputarr[0][0]=0;
}
else if(outputarr[0][5]<0){
outputarr[0][6]=0;
}
else if(outputarr[0][7]<0){
outputarr[0][8]=0;
}
if(outputarr[0][0]>1){
outputarr[0][0]=1;
}
else if(outputarr[0][9]>1){
outputarr[0][10]=1;
}
else if(outputarr[0][11]>1){
outputarr[0][12]=1;
}
//round the calculated right pixal value
right.at<Vec3b>(i,j)[0]=(((outputarr[0][0]))+ float(0.5));
right.at<Vec3b>(i,j)[1]=(((outputarr[0][13]))+ float(0.5));
right.at<Vec3b>(i,j)[2]=(((outputarr[0][14]))+ float(0.5));
newval_4 = left.at<Vec3b>(i,j)[0]; // red
newval_5 = left.at<Vec3b>(i,j)[1]; // Green
newval_6 = left.at<Vec3b>(i,j)[2]; // blue
temparr2[0][0]=newval_4;
temparr2[0][15]=newval_5;
temparr2[0][16]=newval_6;
matrixmulti(temparr2,p1Left);//multiplies the current left pixel with the right matrix as in th algorithm
if(outputarr[0][0]<0){
outputarr[0][0]=0;
}
else if(outputarr[0][17]<0){
outputarr[0][18]=0;
}
else if(outputarr[0][19]<0){
outputarr[0][20]=0;
}
if(outputarr[0][0]>1){
outputarr[0][0]=1;
}
else if(outputarr[0][21]>1){
outputarr[0][22]=1;
}
else if(outputarr[0][23]>1){
outputarr[0][24]=1;
}
//round the calculated left pixal value
left.at<Vec3b>(i,j)[0]=int(((outputarr[0][0])) + float(0.5));
left.at<Vec3b>(i,j)[1]=int(((outputarr[0][25])) + float(0.5));
left.at<Vec3b>(i,j)[2]=int(((outputarr[0][26])) + float(0.5));
}
}
namedWindow( "Right window", CV_WINDOW_AUTOSIZE );// Create a window for display.
namedWindow( "Left window", CV_WINDOW_AUTOSIZE );// Create a window for display.
imshow( "Right window", right );
imshow( "Left window", left );
for (i = 0; i < image.rows; i++)
{
for (j = 0; j < image.cols; j++)
{ //adding out left and right pixel values
image.at<Vec3b>(i,j)[0]=right.at<Vec3b>(i,j)[0]+left.at<Vec3b>(i,j)[0];
image.at<Vec3b>(i,j)[1]=right.at<Vec3b>(i,j)[1]+left.at<Vec3b>(i,j)[1];
image.at<Vec3b>(i,j)[2]=right.at<Vec3b>(i,j)[2]+left.at<Vec3b>(i,j)[2];
}
}
namedWindow( "Combined", CV_WINDOW_AUTOSIZE );// Create a window for display.
imshow( "Combined", image );

Answer 1

Yes, it is a couple of simple vector*matrix multiplications. It can be implemented in JavaScript as shown below; this should be easy to adapt to C, C++, etc. A working JS demo can be found at http://dansted.org/examples/dubois.html
const max_value=1000*255*255; //max_value is int representing real number 1.0.
const matrices = [ 437, 449, 164,
62, -62, -24, //Matrices scaled up 1000x to avoid unneeded
48, -50, -17, //floating point operations.
-11, -32, -7,
377, 761, 9,
-26, -93, 1234 ];
// Here we just convert pixel at co-ordinates (x,y)
var index = (y + x * img_height) * 4;
for (c1 = 0; c1 < 3; c1++) { //rgb: red=0, green=1, blue=2
total_intensity = 0;
for (i = 0; i < 2; i++) { //image[0]: left image, image[1]: right image
intensity = 0;
for (c2 = 0; c2 < 3; c2++) {
input_intensity = images[i][index + c2];
//The following is a quick gamma conversion assuming gamma about 2.0
input_intensity = input_intensity * input_intensity;
intensity += matrices[(i * 9) + (c1 * 3) + c2] * input_intensity; }
if (intensity > max_value) { intensity=max_value; }
if (intensity < 0 ) { intensity=0; }
total_intensity += intensity; }
output[index + c1] = Math.sqrt(total_intensity / 1000); }
output[index + 3] = 255; //Make opaque