Some of the most common lossless compression algorithms are listed below.

Modern systems tend to store the data digitally, often with lossless compression.

It is an inherently lossless compression technique, like almost all entropy-coders.

This extra available non-linear transform can be used to achieve lossless compression.

Lossless compression is possible because most real-world data has statistical redundancy.

Power graph analysis can be thought of as a lossless compression algorithm for graphs.

Lossless compression methods may be categorized according to the type of data they are designed to compress.

A chain code is a lossless compression algorithm for monochrome images.

No information is lost in lossless compression.

(With lossless compression, the almost 4 Gbps of data can be cut nearly in half.)

A compressed format, allows both lossy and lossless compression.

Lossless compression reduces bits by identifying and eliminating statistical redundancy.

After the removal of these details, lossless compression can be applied to the remainder to greatly reduce the file size.

Lossless compression formats enable the original uncompressed data to be recreated exactly.

File size: Unless external lossless compression is applied, the file will take up more space on the computer.

Audiophiles prefer lossless compression formats, but those files are bigger and take longer to download.

Many of the lossless compression techniques used for text also work reasonably well for indexed images.

These files can be combined with lossless compression with the use of file archivers.

Lossless compression should be used to avoid accumulating stages of re-compression when editing images.

Data will typically be compressed with a lossless compression algorithm to minimize the amount of bandwidth used.

By operation of the pigeonhole principle, no lossless compression algorithm can efficiently compress all possible data.

It is a lossless compression technique.

PackBits is a fast, simple lossless compression scheme for run-length encoding of data.

Lossless compression algorithms reduce file size while preserving a perfect copy of the original uncompressed image.

Lossless compression generally, but not exclusively, results in larger files than lossy compression.