Noise reduction in three-dimensional digital images

Two dimensional and three dimensional noise reduction techniques are used on real 3D images and compared. The comparison is based on the busyness of the resulting images and on their fidelity to the original images. The following methods, each with 2D and 3D versions, are reviewed: mean filtering, median filtering, nearest neighbor smoothing, selective averaging and maximum likelihood smoothing. The results suggest that the 3D techniques are more effective at removing noise and retaining image information content than the 2D techniques. The methods that produced the highest quality images were the nearest neighbor and maximum likelihood smoothing techniques. The mean and median filtering methods removed the most noise, but blurred the images. The selective averaging method provided intermediate results.