Image Processing

During image processing, multiple steps are typically executed to achieve the desired final result. Key operations may include image enhancement, image segmentation, feature extraction and classification, and image reconstruction. Image enhancement focuses on improving visual quality through techniques like adjusting brightness, contrast, and sharpness to highlight details - often implemented using histogram equalization or filtering algorithms. Image segmentation partitions images into distinct regions based on characteristics, commonly achieved through thresholding methods like Otsu's algorithm or edge detection techniques. Feature extraction and classification involve identifying and quantifying meaningful patterns using descriptors such as SIFT or HOG, followed by machine learning classification algorithms. Finally, image reconstruction reassembles processed components into either the original image format or generates new visual representations, frequently employing interpolation methods or deep learning architectures like autoencoders.