Abstract/Description
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 remotely sensed images. The technique uses Gaussian low pass filter (GLPF) for generation of slight blur. Then resampling of raster data is performed with the help of bilinear interpolation. Algorithm is developed in MATLAB using some inbuilt functions.
Keywords
Frequency, Image sampling, Sampling methods, Computer errors, Image converters, Computer graphics, Rendering
Location
Crystal Ball Room A, Hotel Pearl Continental, Karachi, Pakistan
Session Theme
Algorithms, Tools and Applications [ALGO-1]
Session Type
Other
Session Chair
Dr. Noor M. Shaikh
Start Date
27-8-2005 6:00 PM
End Date
27-8-2005 6:20 PM
Recommended Citation
Arif, F., & Akbar, M. (2005). A new approach for anti-aliasing raster data in air borne imagery. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2005/2005/34
A new approach for anti-aliasing raster data in air borne imagery
Crystal Ball Room A, Hotel Pearl Continental, Karachi, Pakistan
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 remotely sensed images. The technique uses Gaussian low pass filter (GLPF) for generation of slight blur. Then resampling of raster data is performed with the help of bilinear interpolation. Algorithm is developed in MATLAB using some inbuilt functions.
