Sum image intensities in GPU

Question

I have an application where I need take the average intensity of an image for around 1 million images. It "feels" like a job for a GPU fragment shader, but fragment shaders are for per-pixel local computations, while image averaging is a global operation.

One approach I considered is loading the image into a texture, applying a 2x2 box-blur, load the result back into a N/2 x N/2 texture and repeating until the output is 1x1. However, this would take log n applications of the shader.

Is there a way to do it in one pass? Or should I just break down and use CUDA/OpenCL?

Answer 1

The summation operation is a specific case of the "reduction," a standard operation in CUDA and OpenCL libraries. A nice writeup on it is available on the cuda demos page. In CUDA, Thrust and CUDPP are just two examples of libraries that provide reduction. I'm less familiar with OpenCL, but CLPP seems to be a good library that provides reduction. Just copy your color buffer to an OpenGL pixel buffer object and use the appropriate OpenGL interoperability call to make that pixel buffer's memory accessible in CUDA/OpenCL.

If it must be done using the opengl API (as the original question required), the solution is to render to a texture, create a mipmap of the texture, and read in the 1x1 texture. You have to set the filtering right (bilinear is appropriate, I think), but it should get close to the right answer, modulo precision error.