Remote Sensing Image Enhancement Algorithm for Water Pollution Monitoring Based on Rational Interpolation

Simultaneously increasing the resolution and improving the display quality of the Remote Sensing (RS) imagery, such as water pollution image, is a challenge at present. We propose a new interpolation algorithm based on the rational function model. The model has a free parameter and the shape of the interpolation surface can be modified by using the parameter for the unchanged data. Transformation over triangular domain further improves the interpolation accuracy of the rational function. We divide the image into smooth area and non-smooth area by drawing contour lines and have given full consideration to the directional information of the image edge. Optimization of the parameter makes the interpolation surface more suitable for interpreting the image data directly. The experimental results show that the new techniques not only increase the resolution but also achieve comparative good effects for some RS images.