Last updated: Wednesday 10th September 2008, 7:03 PT, AHD

Image Compression



Image compression is the application of data compression on digital images.
In effect, the objective is to reduce redundancy of the image data in order
to be able to store or transmit data in an efficient form.

Image compression can be lossy or lossless. 
Lossless compression is sometimes preferred for artificial images
such as technical drawings, icons or comics. This is because 
lossy compression methods, especially when used at low bit rates, 
introduce compression artifacts. Lossless compression methods may
also be preferred for high value content, such as medical imagery 
or image scans made for archival purposes. Lossy methods are 
especially suitable for natural images such as photos in applications
where minor (sometimes imperceptible) loss of fidelity is acceptable
to achieve a substantial reduction in bit rate.

The above taken (with permission) from:
Image Compression


Lossy Image Compression


A lossy data compression method is one where compressing data
and then decompressing it retrieves data that may well be different 
from the original, but is "close enough" to be useful in some way. 
Lossy data compression is used frequently on the Internet and 
especially in streaming media and telephony applications. 
These methods are typically referred to as codecs in this context. 
Most lossy data compression formats suffer from generation loss: 
repeatedly compressing and decompressing the file will cause it to 
progressively lose quality. This is in contrast with lossless data compression.
 
The above taken (with permission) from:
Lossy Compression

Scroll down on the Lossy Compression web page
to see an example image compressed by this method.

Lossless Image Compression


Lossless data compression is a class of data compression algorithms
that allows the exact original data to be reconstructed from the compressed data.
This can be contrasted to lossy data compression, which does not allow
the exact original data to be reconstructed from the compressed data.

Lossless data compression is used in many applications. For example, 
it is used in the popular ZIP file format and in the Unix tool gzip.
It is also often used as a component within lossy data compression technologies.

Lossless compression is used when it is important that the original
and the decompressed data be identical, or when no assumption can be made
on whether certain deviation is uncritical. Typical examples are executable programs 
and source code. Some image file formats, notably PNG, use only lossless compression,
while others like TIFF and MNG may use either lossless or lossy methods. 
GIF uses a lossless compression method, but most GIF implementations are incapable
of representing full color, so they quantize the image (often with dithering - see below)
to 256 or fewer colors before encoding as GIF. Color quantization is a lossy process,
but reconstructing the color image and then re-quantizing it produces no additional loss.
(Some rare GIF implementations make multiple passes over an image, adding 255 
new colors on each pass.)

The above taken (with permission) from:
Lossless Compression


Dithering


Dither is a form of noise, or 'erroneous' signal or data 
which is added to sample data for the purpose of minimizing quantization error.
Dither is routinely used in processing of both digital audio and digital video data. 

The above taken (with permission) from:
Dither

Scroll down on the Dither web page
to see dithering examples in digital photography and image processing.







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