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Become a and go ad-free! The short answer ZIPping photographs, music, and videos will typically not make them significantly smaller and can even make them slightly larger. To understand why that might be, we need to look into how compression works at a high level. About compression While the specifics of many different compression algorithms is often the stuff of research, theses, and even, the concepts of compression are actually fairly simple. The idea is that information stored on disk is often stored in a way that is less than optimal for storage. It may be optimal for other purposes, but as a side effect, there may be redundant information in the data that could be represented differently. A simple compression algorithm is “run length encoding.” Consider the following text: This is a row of 10 asterisks:.
![Files Files](/uploads/1/2/5/3/125378711/312233948.jpg)
followed by text. That’s 59 characters long. If we define the character “+” to not be a plus character, but rather an indicator that the next two characters are a count, and the third character the character that should be repeated that many times, we get this: This is a row of 10 asterisks: +10.
followed by text. We’ve shortened or “compressed” the text to only 53 characters, but it still means exactly the same thing. When decompressed, the “+” is encountered causing the “10.” that follows it to be read and replaced with 10 asterisks. The original uncompressed text is restored. This is a row of 10 asterisks:.
followed by text. Doesn’t always compress In the example above, we took a line of 59 characters and “compressed” it to 53 characters. It’s not a great compression algorithm, but it worked.
Now, let’s compress this text using the same algorithm: Here's a single plus sign: + followed by text. That’s 46 characters long. The problem is that because it actually contains the plus sign, the character we said was special in our compression algorithm, we can’t just let it be. If we do, the decompression algorithm will look at it and say, “Oh, the next two characters are a count of the number of times I should repeat the third character following,” which is simply wrong. Unless we specially encode the plus character: Here's a single plus sign: +01+ followed by text. That allowed the decompressor to follow its algorithm: “+” means the next three characters are a count (one, in this case) of the number of times to repeat the third character (“+”).
The compression and decompression algorithm works. The only problem is that the “compressed” data at 49 characters is now larger than the original 46. Every compression algorithm faces this problem. My little example above was crafted to make it easy to show, but even the most advanced compression algorithm will have situations where compressing particular forms of data may cause the “compressed” data to be larger than the original. Compressing already compressed data One of the most common ways that compressed data can end up larger than the original is if the original is itself already compressed. Let’s look at the compressed version of my silly little example again: This is a row of 10 asterisks: +10.
followed by text. What happens if we try to compress that data again? Well, as we saw, that single “+” sign is a problem and needs to be treated specially: This is a row of 10 asterisks: +01+10. followed by text. The result is that the “compressed” data got bigger than the original.
Or rather compressing the already-compressed data made it larger. One of the most common ways that compressed data can end up larger than the original is if the original is itself already compressed.
This happens most reliably when you compress twice using the same algorithm, but if the compression techniques you’re using are relatively efficient, then the algorithms don’t matter as much. ZIPping something twice makes the second zip larger than the first. But ZIPping a “RAR” file, also a compressed file, will typically result in something bigger than the original. With that as background, we can finally explain our answer to the question. Pictures, music, and videos are already compressed Pictures in popular formats such as.jpg,.png. Are already compressed.
Music files in formats like.mp3,.ogg,.aac, and so on are already compressed. Video files in formats like.wmv,.m4v,.mov, and more are already compressed. And as we’ve seen by now, depending on the type of compression you’re using, compressing an already-compressed file at best does very little and at worst makes the file bigger.
So there’s typically no space-saving advantage to ZIPping a photo, a movie, or an MP3. If you have only one copy - it's not backed up. If you delete files to save space on your hard drive make sure that doesn't leave you without a backup.
Windows File Compression automatically compresses files so they take up less space. In the best of circumstances, it can free up a lot of space, but all too frequently it's not as much as you might expect, and there is a cost. Depending on how you look at your disk, the amount of space used can appear quite different. We'll look at some of the possible reasons.
ZIP files are incredibly useful for compressing files and containing collections of files. Unfortunately they're also useful to hackers, spammers and scammers. Posted: October 7, 2012 in: Shortlink: TAGS:. Zipping files that are already in a compressed format (jpg, for example) may save space, but not due to compression savings. Files are allocated in “chunks”. Any space that is left over in the file’s last chunk is effectively wasted space.
The more files, the more wasted space. If you combine all of these files into one archive (zip or otherwise) then you have only the wasted space at the end of the one archive file instead of the waste in each of the component files. However, you have to weigh the space saving against the inconvenience of accessing the files through the archived format.
Also, there is a certain amount of space taken up by the zip file header. It SHOULD be possible to compress an mp3 file to a much smaller size (in a lossless format).
Yes an mp3 file is “compressed” but for a standard constant bitrate file each second of sound is allocated a fixed number of bytes. Most music files will contain repetition, eg a riff or chorus that appears multiple times in the file, and therefore it should be possible, given the right algorithm, to compress out this duplication.
Why this doesn’t happen in reality I guess is that the standard compression algorithms either do not detect this duplication for whatever reason or simply do not deal with it. Maybe someday someone will come up with a totally lossless file compression algorithm for mp3s and even wav, although by then we may all have switched to lossless compression in the first place.
@Earl Purple Here’s the problem with this theory. Lossless compression works by storing symbols using the least number of bits necessary to represent the original data. To put it another way, the data is represented in the compressed file in a highly complex mathematical algorithm that requires less space than the original data. JPGs, GIFs, MP3s, etc, already store their data in a method extremely similar to this. In fact, it has been shows that the Huffman algorithm used in MP3 is a modified version of LZW, an extremely effecient and highly popular compression method. MP3s specifically store music NOT as a compressed waveform, but as a series of coefficients that represent the individual frequencies, or notes, that were present in the original waveform.
In theory, the coefficients would take exactly the same amount of data to store, but MP3 “cheats” in that it throws away any of the coefficients that it thinks people would not be able to hear anyway (perceptual modeling). It then compresses the remaining data as much as possible into the Huffman compression format, and then breaks up the data into individual “frames” that can be played back by MP3 players. In order to make the MP3 file smaller, you can throw away more and more of the frequencies, but you WILL start to hear the degradation in quality rather quickly. JPGs, and MPGs/AVI/etc, have similar concepts behind them. You mentioned that it should be possible to remove the repetition in the riffs, and repeated parts to save more space, but consider this: if you play the same note with an instrument one million times, you will NEVER be able to find two identical waveforms in them!
There is far too much randomness to the data for that type of compression to be possible. And it would make no difference if you found two “similar” notes, and somehow subtracted out the differences so you could save the space of the actual second note and just store the tiny differences between the notes. There is so much randomness to the differences that it would take essentially the same amount of space in the file to do that. Actually, MIDI does something similar to this, instead of storing the sound from the instruments, it just stores what notes are played and recreates that sound upon playback.
It is NEVER going to sound like the “real thing” because you aren’t storing the real waveform, just the information that there was a note played. If you would like more info on how compresion works, check out Wikipedia’s article: -cheers. Earl: All those riffs that you think could be replaced by one copy, cannot. There are differences in the playing of them every time, even though the sheet music might be the same. Consider the Smoke on the Water riff. Even on the sheet music, it has variations, then you add in the ones that come from a real person playing it. The problem with your other theory of a loss less way to compress MP3s is that the MP3 has already created losses and if you could find your magical program, you are just copying the losses.
However, as Leo tried to explain (and did a much better job than most of the explanations I have seen), a compessed file looks to another compressor as relatively random stuff that doesn’t compress well. Don’t ever expect that any program will compress any already compressed (even a lossless) file. FLAC compression is lossless and does a great job in compressing audio files that were not already compressed by something else. You could compress them more by converting them to an MP3 but what that would really be doing is restoring the uncompressed audio and throwing out parts of it that you think are not really noticeable as it compresses it again. If you want to experiment with something more obvious than audio (a lot of the changes are very subtle), try using a program where you can convert a photo to jpg and adjust the compression. Pick a photo with some subtle shading of similar colors (like sky) or for a shocker, use some line art (like a screen capture of this page) to see how much the compression looses or modifies the origonal.
The algorithm described in the article is lossless, the ten asterisks are returned intact. Years ago pondering file compression I figured something like that independently. (I have re-invented the wheel hundreds of times, can’t help it) I do a lot of intense graphics work, and I always save my files as bitmaps.
(Or vector graphics if they are of that nature) but never as jpg. (Unless I get careless and do it by mistake, which happens sometimes) Disk space is not that precious to me anyway, and a lot of times I will attach a bmp to an email, then wonder if the recipient will wonder why I didn’t send a jpg. If you save a 256 color image as a jpg and then test the count of colors in the picture, it will be in the tens of thousands. If you cut a figure out of the background by filling the backgournd with white, then save the cut out figure as a jpg, and later try to paste that cut out figure over a new background, it won’t work, because the white will have become a hundred or more ‘shades’ of white.
I am now curious enough to test a compression program like 7zip on a bmp file, although I doubt I would use it even if it results in high compression and no loss of data. Maybe for archiving some old files to DVDs or something. Thanks for giving me something to think about. It’s great being a geek in the company of geeks. ZIPping several less used files has a different benefit. It reduces the folder and file names clutter. And reduces the number of file handles (or inodes in Linux).
![The bonez astronaut rar files online The bonez astronaut rar files online](http://www.pngmart.com/files/5/Astronaut-Transparent-PNG.png)
File handles or inodes are the index entries for a file on the file system. And, these are not unlimited. Moreover, it can decrease the computer’s performance/response when searching or using file explorers. So, if you have many files that you use rarely, it is good to organize them in folders and ZIP each folder and then delete the files. Also, when you need to store a large number of files on a USB external hard disk, it reduces the backup time.
Storing one or few zip files takes substantially lesser time than storing thousands of files. Before commenting please:. Read the article. Comments indicating you've not read the article will be removed. Comment on the article. New question?
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