Compression algorithms for speech, audio, still images, and video are quite complicated and, more importantly, nearly always lossy. Thus, samples often change dramatically once they’re decompressed.

Compression reduces bandwidth and storage requirements by removing redundancy and irrelevancy. Redundancy occurs when data is sent when it’s not needed. Irrelevancy frequently occurs in audio and ...

The goal of digital compression algorithms is to produce a digital representation of an audio signal which, when decoded and reproduced, sounds the same as the original signal, while using a minimum ...

A 3.0X times image compression method and fast storage device accessing H.265 referencing image frame is achieved by applying fixed bit rate to reduce each “Block of pixels” data of each image frame.

Optimizing data compression methods has become more critical than ever for cloud storage, data management, and streaming applications. Working with compressed data reduces network bandwidth, data ...