tömörítéskompresszió

tömörítéskompresszió is a term used in data storage and transmission to describe the reduction of redundancy in digital files. The process is achieved through encoding algorithms that replace frequently recurring patterns with shorter representations, thereby decreasing the overall file size. The two main categories of tömörítéskompresszió are lossless and lossy compression. Lossless methods preserve all original data, making them suitable for text, executable programs, and medical imaging where precision is critical. Representative algorithms in this category include the Lempel–Ziv family, Run‑Length Encoding, and Huffman coding. Lossy techniques discard or approximate certain details that are less perceptible to the human eye or ear, enabling larger reductions. JPEG for still images, MP3 for audio, and certain video codecs such as H.264 and H.265 exemplify lossy compression. The choice of algorithm depends on factors such as required fidelity, computational resources, and the specific data domain. Contemporary research in tömörítéskompresszió explores adaptive models, machine learning–based predictors, and the integration of compression with encryption to increase both efficiency and security. While compression is indispensable for efficient storage and bandwidth usage, it also poses challenges such as increased computational cost, potential loss of data integrity, and the need for standardized decoding formats to ensure interoperability.