Digital image processing refers to the manipulation and analysis of digital images using computer algorithms. It involves various techniques and operations to enhance, transform, and extract information from digital images. These techniques can be applied to images captured by digital cameras, scanned documents, satellite imagery, or any other form of digital image.
Here are some common tasks and techniques in digital image processing:
Image enhancement: Techniques such as brightness adjustment, contrast stretching, and histogram equalization are used to improve the visual quality of images and highlight important details.
Filtering: Filtering operations like smoothing (e.g., Gaussian blur) and sharpening (e.g., unsharp masking) are applied to remove noise, blur, or enhance image details.
Image restoration: Methods for restoring degraded or damaged images, including techniques for noise reduction, deblurring, and removal of artifacts.
Image compression: Algorithms such as JPEG and PNG are used to reduce the size of digital images for storage and transmission purposes while preserving the perceptual quality to a certain extent.
Image segmentation: The process of partitioning an image into multiple regions or objects based on their characteristics, such as color, texture, or intensity. Segmentation is often a crucial step in object recognition and computer vision tasks.
Object detection and recognition: Techniques to identify and locate specific objects or patterns within an image, often involving machine learning algorithms such as convolutional neural networks (CNNs).
Image registration: Aligning multiple images of the same scene taken at different times or from different viewpoints to create a composite image or perform image comparison.
Morphological operations: Mathematical operations, such as dilation (expanding object boundaries) and erosion (shrinking object boundaries), used for shape analysis and processing.
Feature extraction: The process of extracting meaningful features or descriptors from images, often used for pattern recognition, image classification, and object tracking.
Geometric transformations: Operations such as rotation, scaling, translation, and perspective correction used to modify the spatial properties of an image.
These are just a few examples of the wide range of techniques and applications within digital image processing. The field is interdisciplinary, combining principles from mathematics, statistics, signal processing, and computer science to analyze and manipulate digital images.
