Digital Image Processing (DIP) encompasses a series of operations aimed at enhancing the quality and analytical value of digital images.
The initial phase is image acquisition, the process of capturing images via sensors or scanners and digitizing them.
Subsequently, pre-processing addresses issues such as distortion correction, noise reduction, and enhancement to improve visual fidelity.
Image segmentation is performed to partition the image into distinct, interpretable regions or objects.
This is followed by image classification, wherein pixels are assigned to predefined classes based on their spectral characteristics.
Post-processing might include filtering, smoothing, or integrating results to boost precision.
Lastly, information extraction and interpretation transform the processed data into actionable insights for decision support.
Collectively, these stages convert raw imagery into valuable and meaningful data.