Image aliasing is a problem appearing as artefacts in digitally resampled images, which degrades the quality of the image. In digital rectification and texture mapping, pixels from an input image are transformed to pixels of an output image. The discrete nature of a digital image causes aliasing in the transformed image. In this paper the source of aliasing and the theory of antialiasing are described. The necessity of a precise filter design in antialiasing is discussed and a filter based on a Kaiser adjustable window is designed. Different practical antialiasing methods are described as well as interpolation methods, which are conventional in photogrammetry. Selected antialiasing methods are implemented and applied to a close range image. An objective analysis is carried out by applying inverse transformations to rectified images and deriving some measures to estimate the information loss for each method by comparing original and reconstructed images. Results indicate that interpolation methods are not capable of removing or reducing aliasing in highly decimating transformations. The output images of interpolation methods therefore suffer from edge corruption and interfusion of small features. Applying a Kaiser filter with a precise antialiasing method results in the least information loss and considerably reduces aliasing at the expense of higher computation load.
- Digital photogrammetry
- Kaiser filter