Lets talk compressing types
lossy compression or
irreversible compression is the class of data encoding methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size but will also degrade the image as the original pixel data is gone
Lossless compression is a method of data compression in which the size of the file is reduced without sacrificing image quality. Unlike lossy compression, no data is lost when this method is used. Because the data is preserved, the technique will decompress the data and restore it exactly to its original state.
Can be uncompressed
without data loss
Compressed down to 17%
Run-length encoding (RLE) is a very simple form of lossless data compression in which runs of data 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 mostly black pixels. It is not useful with files that don't have many runs as it could greatly increase the file size.
When should you compress?
Any media being introduced into the workflow should always be data checked and if needed re-saved into a lossless format. Formats which contain proprietary formats ( PSD, Tiff, etc. ) should have a Master and production version.
CONVERT TO LOSSLESS ► ► ►
► ► ► ALWAYS LOSSLESS ► ► ►
NORMALLY LOSSY ► ► ►
If your client is just viewing images then lossy is ok. This allows them to view it on websites and most computers quickly.
Client should always receive a master version that is not lossy.
Lossless will allow compressing while not losing any data.
Basic Video Compression
a : b : c
a = Pixels across are sampled (YUV)
b = Pixels across have there own chroma (U+V)
c = In row 2 that have there own chroma (U+V)
No compression and transports both luminescence and color data entirely
Half the sampling rate horizontally, but will maintain full sampling vertically.
Sample colors out of half the pixels on the first row and ignores the second row of the sample completely.