A new approach for anti-aliasing raster data in air borne imagery
Fahim Arif, Muhammad Akbar · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Air borne sensed data is in the form of raster data. Aliasing is always present in a sampled image causing artifact error. To reduce possible aliasing effects, it is a good idea to blur an image slightly before applying a resampling method on it. This paper presents a technique for anti-aliasing air borne sensed images. The technique uses Gaussian low pass filter (GLPF) for generation of slight blur and reduction of high frequency components. Then resampling of raster data is performed with the help of bilinear interpolation. Algorithm is developed in MATLAB using some inbuilt functions. The method is applied on different types of images, and their frequency spectrum and histogram analysis is carried out.