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GPU Accelerated Image Processing

Alark Joshi


With the advent of hardware accelerated graphics card, the ability to perform parallelizable tasks on the graphics card makes it easy to accelerated common image processing tasks. NVIDIA's Cg (C for Graphics) language allows the ability to write high level programs (shaders) that allow access to graphics memory. The strength of using Cg, when it was introduced, was the seamless integration with OpenGL and DirectX and allowed for easy interaction with the graphics hardware. With the availabilty of CUDA, and OpenCL now, the graphics cards are more accessible and allow for parallelization of time consuming computationally expensive tasks. A CUDA-based version of this utility is in the works and shall be available shortly.



An easy to use hardware accelerated image processing utility. The code is written in C++ and the shaders are in Cg.