bildebehandlingsfunksjon

Bildebehandling, commonly known in English as image processing, refers to the manipulation and analysis of digital images using computer algorithms. It covers a broad range of techniques designed to improve image quality, extract information, or transform images for display or storage. The field is distinct from computerized imaging in hardware; it focuses on software-based processing of image data.

Image processing can be categorized into enhancement, restoration, analysis, and compression. Enhancement improves visual quality or emphasizes features, while restoration aims to reverse degradation caused by imaging systems. Analysis includes feature extraction, segmentation, pattern recognition, and measurement. Compression reduces the amount of data required to store or transmit images, often with trade-offs between quality and size.

Techniques are typically grouped into spatial-domain methods, which operate on pixel values directly, and frequency-domain methods, which manipulate image representations such as Fourier or wavelet coefficients. Common operations include filtering to reduce noise or sharpen edges, interpolation for resizing, edge detection, color-space conversion, and histogram equalization. Modern work often combines machine learning with traditional methods, training models to classify, segment, or synthesize images.

A typical processing pipeline includes acquisition, preprocessing, processing, and post-processing, supported by representations such as grayscale or color images with varying resolution and bit depth. Applications span photography, medical imaging, remote sensing, surveillance, and computer vision, each with specific goals, metrics, and constraints. Challenges include artifacts, evaluation standards, computational demands, and ethical considerations around privacy and bias.