What is lzw image compression

LZW compression sometimes resulted in a larger file than the original. Zip compression was uniformly more effective than LZW compression.

Base image properties size, colours were retained. Decompressed files were not always the same size as the original. File size comparison of most compressible vs least compressible image in sample. The next steps These results were interesting in themselves but also led us to explore more deeply.

Watch this space for news! Compression TIFF. Read more from Kevin Davies. You might also like…. Join the conversation. Member-only content. You are trying to access member content. There are of them, numbered 0 through , since our characters are bytes. WriteCode writes a code to the output stream. The first code written is a Clear code, which is defined to be code Omega is our "prefix string.

This will be number between 0 and , since our characters are bytes. AddTableEntry adds a table entry. InitializeStringTable has already put entries in our table. Each entry consists of a single-character string, and its associated code value, which is, in our application, identical to the character itself. So the first entry that we add to our string table will be at position , right?

Well, not quite, since we will reserve code for a special "Clear" code, and code for a special "EndOfInformation" code that we will write out at the end of the strip.

So the first multiple-character entry added to the string table will be at position Let's try an example. Of course, since all single character strings were put in the table by InitializeStringTable.

Read Pixel 1 into K. No, so we get to do some real work. Note that although we have added the string consisting of Pixel 0 and Pixel 1 to the table, we "re-use" Pixel 1 as the beginning of the next string.

Back at the top of the loop. We read Pixel 2 into K. We read Pixel 3 into K. We read Pixel 4 into K. When we are just starting out, we can use 9-bit codes, since our new string table entries are greater than but less than But when we add table entry , we must switch to bit codes. Likewise, we switch to bit codes at , and bit codes at We will somewhat arbitrarily limit ourselves to bit codes, so that our table can have at most entries. If we push it any farther, tables tend to get too large.

What happens if we run out of room in our string table? This is where the afore-mentioned Clear code comes in. As soon as we use entry , we write out a bit Clear code. If we wait any dworder to write the Clear code, the decompressor might try to interpret the Clear code as a bit code. At this point, the compressor re-initializes the string table and starts writing out 9-bit codes again. Note that whenever you write a code and add a table entry, Omega is not left empty. It contains exactly one character.

Be careful not to lose it when you write an end-of-table Clear code. You can either write it out as a bit code before writing the Clear code, in which case you will want to do it right after adding table entry , or after the clear code as a 9-bit code. Decompression gives the same result in either case.

To make things a little simpler for the decompressor, we will require that each strip begins with a Clear code, and ends with an EndOfInformation code. Every LZW-compressed strip must begin on a byte boundary. It need not begin on a word boundary. LZW compression codes are stored into bytes in high-to-low-order fashion, i.

The compressed codes are written as bytes, not words, so that the compressed data will be identical regardless of whether it is an "II" or "MM" file. Note that the LZW string table is a continuously updated history of the strings that have been encountered in the data. It thus reflects the characteristics of the data, providing a high degree of adaptability.

LZW is the foremost technique for general-purpose data compression due to its simplicity and versatility. How does it work? LZW compression works by reading a sequence of symbols, grouping the symbols into strings, and converting the strings into codes. Because the codes take up less space than the strings they replace, we get compression. Characteristic features of LZW includes, LZW compression uses a code table, with as a common choice for the number of table entries.

Codes in the code table are always assigned to represent single bytes from the input file. When encoding begins the code table contains only the first entries, with the remainder of the table being blanks. Compression is achieved by using codes through to represent sequences of bytes.

As the encoding continues, LZW identifies repeated sequences in the data and adds them to the code table. Decoding is achieved by taking each code from the compressed file and translating it through the code table to find what character or characters it represents. Typically, every character is stored with 8 binary bits, allowing up to unique symbols for the data.

This algorithm tries to extend the library to 9 to 12 bits per character. The new unique symbols are made up of combinations of symbols that occurred previously in the string. It does not always compress well, especially with short, diverse strings. But is good for compressing redundant data, and does not have to save the new dictionary with the data: this method can both compress and uncompress data. Implementation The idea of the compression algorithm is the following: as the input data is being processed, a dictionary keeps a correspondence between the longest encountered words and a list of code values.

The words are replaced by their corresponding codes and so the input file is compressed. Therefore, the efficiency of the algorithm increases as the number of long, repetitive words in the input data increases.

There is another variation of 6 different versions here. In other words, if the image is 8 bits go LZW and if it is 16 bits go with ZIP, as a rule of thumb, but with the caveat that it's not an absolute rule and there may be exceptions. While that's probably more than enough time for it to no longer be an issue, there may be the odd piece of software out there that handles LZW compression but not ZIP. Compression is something you can see yourself, so I'll focus on interoperability and long-term preservation.

I did find problematic TIFF files whose compression upset my open-source program in the past, but I don't remember what was the exact culprit. LZW was patented until Make sure not to introduce some data loss yourself. For the fastest save times you want to go with no compression. Sign up to join this community. The best answers are voted up and rise to the top.

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