Resampling air borne sensed data using bilinear interpolation algorithm

Air borne sensed data is gained by satellite/aerial images and other remote sensing or scanning platforms. Each grid-cell, or pixel, has a certain value depending on how the image was captured and what it represents. Reprojection and resampling of raster image data should be handled with caution. Issues of geometric distortions and errors due to resampling need to be considered carefully. Interpretation of such data requires correction of distortions and resampling of recorded data. There are different methods for this purpose but they have their inbuilt problems as well. This paper presents a bilinear interpolation method for resampling of air borne sensed data. The method is developed in Matlab and results are obtained using different interpolation rates. A review of the used method is also given at the end.