Raster Data Processing Techniques

Raster data represents information about the Earth's surface as a grid of cells (pixels), where each cell stores a value that represents a feature or attribute.

Image Resampling: Adjusting the resolution of an image by rescaling pixels. Useful for aligning images with different resolutions or merging images of different sizes.
Image Enhancement: Techniques to improve the quality or interpretability of images, such as contrast enhancement, sharpening, and color balancing.
Image Mosaicking: Combining multiple images to create a seamless composite image of a larger area. Essential for creating continuous coverage over large regions.
Geometric Correction: Adjusting satellite images to correct distortions caused by Earth's curvature and satellite sensor position. Includes orthorectification for accurate geographic representation.
Atmospheric Correction: Removing atmospheric effects (such as scattering and absorption) from satellite images to improve the accuracy of remote sensing data analysis.
Noise Removal: Filtering techniques to reduce unwanted variations in image data caused by sensor noise, interference, or environmental factors.