Removing noise from an image using techniques such as median filtering, Gaussian filtering, or wavelet transform.
Identifying objects in an image using techniques such as edge detection, feature extraction, and machine learning algorithms.
Dividing an image into different regions or segments based on common properties such as color, texture, or intensity.
Restoring degraded or damaged images using techniques such as deblurring, super-resolution, or inpainting.
Identifying faces in an image using techniques such as Haar cascades, deep learning, or eigenfaces.
Combining multiple images into a single panoramic image using techniques such as feature matching, homography estimation, and blending.
Reducing the size of an image while preserving its quality using techniques such as discrete cosine transform, wavelet transform, or fractal compression.
Aligning two or more images taken at different times or from different viewpoints using techniques such as affine transformation, non-rigid transformation, or mutual information.
Extracting text from an image using techniques such as edge detection, binarization, and machine learning algorithms.
Finding images in a database that are similar to a given query image using techniques such as content-based image retrieval, texture analysis, or color histograms.