Editing Lossless compression (section)

=== Historical legal issues ===
Many of these methods are implemented in open-source and proprietary tools, particularly LZW and its variants. Some algorithms are patented in the [[United States]] and other countries and their legal usage requires licensing by the patent holder. Because of patents on certain kinds of [[Lempel–Ziv–Welch|LZW]] compression, and in particular licensing practices by patent holder Unisys that many developers considered abusive, some open source proponents encouraged people to avoid using the [[Graphics Interchange Format]] (GIF) for compressing still image files in favor of [[Portable Network Graphics]] (PNG), which combines the [[LZ77 and LZ78|LZ77]]-based [[Deflate|deflate algorithm]] with a selection of domain-specific prediction filters. However, the patents on LZW expired on June 20, 2003.<ref>{{cite web |url=http://www.unisys.com/about__unisys/lzw |publisher=Unisys |title=LZW Patent Information |website=About Unisys |url-status=dead |archive-url=https://web.archive.org/web/20090602212118/http://www.unisys.com/about__unisys/lzw |archive-date=2009-06-02 }}</ref>

Many of the lossless compression techniques used for text also work reasonably well for [[indexed image]]s, but there are other techniques that do not work for typical text that are useful for some images (particularly simple bitmaps), and other techniques that take advantage of the specific characteristics of images (such as the common phenomenon of contiguous 2-D areas of similar tones, and the fact that color images usually have a preponderance of a limited range of colors out of those representable in the color space).

As mentioned previously, lossless sound compression is a somewhat specialized area. Lossless sound compression algorithms can take advantage of the repeating patterns shown by the wave-like nature of the {{nowrap|data{{px2}}{{mdash}}{{px2}}}}essentially using [[autoregressive]] models to predict the "next" value and encoding the (possibly small) difference between the expected value and the actual data. If the difference between the predicted and the actual data (called the ''error'') tends to be small, then certain difference values (like 0, +1, −1 etc. on sample values) become very frequent, which can be exploited by encoding them in few output bits.

It is sometimes beneficial to compress only the differences between two versions of a file (or, in [[video compression]], of successive images within a sequence). This is called [[delta encoding]] (from the Greek letter [[delta (letter)|Δ]], which in mathematics, denotes a difference), but the term is typically only used if both versions are meaningful outside compression and decompression. For example, while the process of compressing the error in the above-mentioned lossless audio compression scheme could be described as delta encoding from the approximated sound wave to the original sound wave, the approximated version of the sound wave is not meaningful in any other context.