MARCOS AND ALBERTO by Alberto Martín MOR

Lossless and lossy compression differences.

marcoshu — 2015-09-30 15:43:28 UTC

Lossless and lossy compression. Lossless compressionis a class of data compression algorithms that allows the original data to be perfectly reconstructed from the compressed data. Lossy compressionis the class of dataenconding methods that uses inexact approximations (or partial data discarding) to represent the content. For the first compression, we are going to use the datacompression program called WinRar. You can download WinRar on the next link: https://www.winrar.es/descargas

In the first video, I am going to prove if a compressed file and the uncompressed file with WinRar have any differences

marcoshu — 2015-09-30 15:44:27 UTC

In the second video, I am going to explain the diferences after a lossy compression between a mp3 file and a WAV file.

marcoshu — 2015-09-30 16:09:33 UTC

BACKGROUND COLOR

albertm1 — 2015-10-01 17:53:18 UTC

Its a blueish color made by us in paletton.

http://paletton.com/#uid=14w0u0kDDGH1IQ6lkG3LHojX-bd

marcoshu — 2015-10-01 17:54:37 UTC

Here as you can see, is the differences between a compressed file with a lossy compressor and the original file

marcoshu — 2015-10-01 17:55:03 UTC

!) What is the compression ratio?

albertm1 — 2015-10-01 17:55:11 UTC

Data compression ratio, also known as compression power, is a computer science term used to quantify the reduction in data-representation size produced by a data compression algorithm. The data compression ratio is analogous to the physical compression ratio used to measure physical compression of substances.

Data compression ratio is defined as the ratio between the uncompressed size and compressed size:

2)Is there a limit to the compression ratio?

albertm1 — 2015-10-01 17:57:05 UTC

Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but can rarely do much better than 1/2 compression because of the intrinsic entropy of the data. (50% of compression ratio)

Lossy Compression

Video can be compressed immensely (e.g. 100:1) with little visible quality loss
Audio can often be compressed at 10:1 with imperceptible loss of quality
Still images are often lossily compressed at 10:1, as with audio, but the quality loss is more noticeable, especially on closer inspection

There is no limit, that means that every time you loose more and more infirnation, at one point the message its going to be so compressed that you wont be able too understand it.

marcoshu — 2015-10-01 17:59:48 UTC

There is an example while compressing files in which in the 2 bars it says the compression ratio and how much was compressed.

marcoshu — 2015-10-01 18:00:15 UTC

albertm1 — 2015-10-01 18:01:29 UTC

albertm1 — 2015-10-01 18:01:52 UTC

3)What happens if you try to compress the same file more than one time?

albertm1 — 2015-10-01 18:07:44 UTC

For lossless compression, the only way you can know how many times you can gain by recompressing a file is by trying. It's going to depend on the compression algorithm and the file you're compressing.

Two files can never compress to the same output, so you can't go down to one byte. How could one byte represent all the files you could decompress to?

The reason that the second compression sometimes works is that a compression algorithm can't do omniscient perfect compression. There's a trade-off between the work it has to do and the time it takes to do it. Your file is being changed from all data to a combination of data about your data and the data itself.

Example

Take run-length encoding (probably the simplest useful compression) as an example.

04 04 04 04 43 43 43 43 51 52 11 bytes

That series of bytes could be compressed as:

[4] 04 [4] 43 [-2] 51 52 7 bytes (I'm putting meta data in brackets)

Where the positive number in brackets is a repeat count and the negative number in brackets is a command to emit the next -n characters as they are found.

In this case we could try one more compression:

[3] 04 [-4] 43 fe 51 52 7 bytes (fe is your -2 seen as two's complement data)

We gained nothing, and we'll start growing on the next iteration:

[-7] 03 04 fc 43 fe 51 52 8 bytes

We'll grow by one byte per iteration for a while, but it will actually get worse. One byte can only hold negative numbers to -128. We'll start growing by two bytes when the file surpasses 128 bytes in length. The growth will get still worse as the file gets bigger.

There's a headwind blowing against the compression program--the meta data. And also, for realcompressors, the header tacked on to the beginning of the file. That means that eventually the file will start growing with each additional compression.

Lossy Compression

If you compress the same file repetidly, at one point the information is going to disappear

Here is a demonstration to the answer of Anselmo

marcoshu — 2015-10-01 18:15:13 UTC

https://youtu.be/7k4zAWcxC5M