programming-for-dummies

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Lossy Data Compression
Video basically saves successive still images, so lossy compression can save
space by looking for identical backgrounds between video frames. Rather than
store the same background multiple times, lossy compression stores the background
only once and uses that identical image multiple times. Because the
same background may appear in several video frames, this technique can
shrink the size of a video considerably.
Another way to compress data is to alter the bit depth. Bit depth defines how
many bits are used to store data, such as 96-bit or 160-bit. The more bits
used, the greater the quality but the larger the file size. The fewer bits used,
the less storage space required and the less data saved, reducing the file
size. That’s why a 96-bit MP3 file is smaller than the same file saved as a 160-
bit MP3 file. The 96-bit file can’t store as much data as the 160-bit file, which
means lower audio quality than the 160-bit file.
When compressing a file, lossy compression may use constant bit rate (CBR)
or variable bit rate (VBR) compression. CBR reduces the bit rate uniformly
throughout the entire file and makes compression faster. Unfortunately, this
also means that silent portions of an audio file get compressed at the same
rate as noisier parts of the audio file, resulting in less-than-optimum
compression.
VBR alters the bit rate, depending on the complexity of the data. This improves
quality but at the cost of a slower compression time. For even higher quality,
some compression algorithms offer two-pass VBR, which means the program
analyzes the file twice to get the maximum quality and the smallest file size
possible, but at the expense of much slower compression speed.
All types of compression are always a trade-off. With lossless compression,
the trade-off is between size and speed. The smaller you want to compress
the file, the longer it takes. With lossy compression, the trade-off is mostly
between size and quality. The smaller the file size, the lower the overall quality.
Both lossless and lossy compression algorithms are necessary, depending
on which type better suits your needs.