Run-length encoding (part I)

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Run-length encoding RLE is a very simple form of lossless data compression in which runs of data that is, sequences in which binary run length encoding compression same data value occurs binary run length encoding compression many consecutive data elements are stored as a single data value and count, rather than as the original run. This is most useful on data that contains many such runs. Consider, for example, simple graphic images such as icons, line drawings, and animations.

It is not useful with files that don't have many runs as it could greatly increase the file size. RLE may also be used to refer to an early graphics file format supported by CompuServe for compressing black and white images, but was widely supplanted by their later Graphics Interchange Format.

RLE also refers to a little-used image format in Windows 3. For example, consider a screen containing plain black text on a solid white background. There will be many long runs of white pixels in the blank space, and many short runs of black pixels within the text.

A hypothetical scan linewith B representing a black pixel and W representing white, might read as follows:. With a run-length encoding RLE data compression algorithm applied to the above hypothetical scan line, it can be rendered as follows:. The run-length code represents the original 67 characters in only While the actual format used for the storage of images is generally binary rather than ASCII characters like this, the principle binary run length encoding compression the same.

Even binary data files can be compressed with this method; file format specifications often dictate repeated bytes in files as padding space. Run-length encoding can be expressed in multiple ways to accommodate data properties as well as additional compression algorithms. For instance, one popular method encodes run lengths for runs of two or more characters only, using an "escape" symbol to identify runs, or using the character itself as the escape, so that any time a character appears twice it denotes a run.

On the previous example, this would give the following:. This would be interpreted as a run of twelve Ws, a B, a run of twelve Ws, a run of three Bs, etc. In data where runs are less frequent, this can binary run length encoding compression improve the compression rate.

One other matter is the application of additional binary run length encoding compression algorithms. Even with the runs extracted, the frequencies of different characters may be large, allowing for further compression; however, if the run lengths are written binary run length encoding compression the file in the locations where the runs occurred, the presence of these numbers interrupts the normal flow and makes it harder to compress.

To overcome this, some run-length encoders separate the data and binary run length encoding compression symbols from the run lengths, so that the two can be handled independently. Run-length encoding schemes were employed in the transmission of television signals as far back as The ITU also describes a standard to encode run-length-colour for fax machines, known as T.

From Wikipedia, the free encyclopedia. Not to be confused with run-length limited. Proceedings of the IEEE. Compression formats Compression software codecs. Multimedia compression and container formats. See Compression methods for methods and Compression software for codecs. Retrieved from " https: All articles with unsourced statements Articles with unsourced statements from December Views Read Edit View history. This page was last edited on 18 Decemberat By using this site, you agree to the Terms of Use and Privacy Policy.

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This is part 1, there is also a part 2 and a part 3. Run-length encoding RLE is probably the most important and fundamental string compression technique. Countless multimedia formats and protocols use one form or RLE compression or another. RLE is also deceptively simple. It represents repeated values as a counter and a character.

If that is all there was to RLE, then the wikipedia page on run-length encoding would be just fine. Yet, I think it needs help. There is no unique RLE format. How you use the RLE idea depends on your goals such as 1 maximize the compression rate 2 maximize the processing speed. Continue reading to part 2. Thanks Daniel for the beautifully concise explanation of RLE. Makes me wonder how it can seem complex in other explanations. I could try to guess what iterated hierarchical RLE with a fancy encoding means, but that is not a very interesting game.

As I told you this is something I stumbled upon when peeking at reverse engineering of a compression utility. Kevembuangga Let me put it differently. Could you implement the a scheme like the one you described? Your email address will not be published. For more help see http: Skip to content My home page My papers My software. Why do we use RLE? You can read and write RLE data in one pass, using almost no memory.

Given a vector V compressed with RLE, you can apply any scalar function f to its component in time O V where V is the compressed size of the vector. Some RLE formats have worse complexity bounds. Any downsides to RLE? Random access is slower. Sometimes, only sequential read from the beginning is possible. Updating an RLE-compressed array can be difficult. You need long runs of identical values.

Thus, if the compression rates are modest, it could actually take longer to process an RLE-compressed array. What is the RLE format? Here are some common variations: Instead of using a counter for each run of characters, you only add a counter after a value has been repeated twice. Thus, if many characters are not repeated, you will rarely use an unnecessary counter. You can use a single bit to decide whether a counter is used. Again, this may avoid many unnecessary counters if values are often not repeated.

Instead of a counter, you may store the location of the run in the array. The benefit of this approach is to allow random access in logarithmic time using binary search. However, it is also incompatible with some techniques to avoid unnecessary counters. So, it is a compression-speed trade-off. For even more speed, you can store both the location of the run and its length thus avoiding a subtraction.

To help vectorization , you can group the characters into blocks of k characters. Again, this is a compression-speed trade-off because there will be fewer runs to compress after grouping the characters into long blocks. Some References to my own work: Leave a Reply Cancel reply Your email address will not be published.

To create code blocks or other preformatted text, indent by four spaces: This will be displayed in a monospaced font. Markdown is turned off in code blocks: More database compression means more speed? Run-length encoding part 2.