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GPU-Accelerating Denoising in 3D (GD3D) is an open-source implementation in CUDA of three commonly used image denoising methods: bilateral filtering, anisotropic diffusion, and non-local means. It was written to study the performance characteristics of these methods on 3D magnetic resonance images, as described in the paper:

Howison M and Bethel EW. GPU-accelerated denoising of 3D magnetic resonance images. (under review)

Installation

Download the latest version from Bitbucket. The only prerequisite is the CUDA Toolkit 5.0.35. You may need to adjust the variable CUDA_DIR in the Makefile to point to your CUDA installation. Also, you may need to change the line:

LIBS = -L$(CUDA_DIR)/lib -lcudart -lm

to

LIBS = -L$(CUDA_DIR)/lib64 -lcudart -lm

to build on a 64-bit Linux system (the included line should work on OS X).

The Makefile will build six executables:

sweep/aniso
sweep/bilat
sweep/nlm
tune/aniso
tune/bilat
tune/nlm

The sweep executables perform a parameter sweep to determine optimal smoothing parameters, while the tune exceutables perform an auto-tuning study to deterermine optimal memory blocking (see the paper for details).

License

GD3D is distributed under a modified BSD license. See LICENSE for full details.