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image compression

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on 3 March 2013

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Transcript of image compression

Image compression Introduction to Digital image
Images are composed of either pixels, vector (geometric) data or a combination of the two Theories REFERENCES strengths/weaknesses The pixel The Vector smallest addressable
screen element result of mathematical function;
made up of linear paths, which lead through "control" points Image compression the main purpose of image compression is to reduce irrelevance and redundancy of the image data in order to store or transmit data in an efficient form. Lossless vs. Lossy Compression Framework lossless lossy Image formats Raster Formats Vector formats jpeg bmp gif tiff exif png raw others others svg RS-274x cgm JPEG COMPRESSION Original image
File size: 192 KB Lossy compression
File size: 93 KB Original .jpg
saved at 100% quality TIFF compression strengths weaknesses JPEG about Lossy chops the file into small segments (to reduce download time for example), transformed and quantised. The reduced files are then encoded. This, however is not a reconstruction of the original, but "close enough" to be useful.
Lossy data compression is used frequently on the Internet and especially in streaming media and telephony applications.
Better compression ratio Lossless compression algorithms allow 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.
No quality loss lwf about compressions TIFF not displayed in many browsers
large size (hard to store and transfer) recommended for shooting the image
multiple saves don't affect quality format of choice for the web
it can achieve great compression ratios multiple saves and compression reduces quality
shouldn't be used for line art; such images with areas of uniform colours and sharp edges, jpeg is unsuitable TIFF is, in principle, a very flexible format that can be lossless or lossy. The details of the image storage algorithm are included as part of the file.
In practice, TIFF is used almost exclusively as a lossless image storage format that uses no compression at all. Most graphics programs that use TIFF do not compress. Consequently, file sizes are quite big.
A lossless compression algorithm called LZW is used (but it is not universally supported) Statistical modelling algorithms for text (or text-like binary data such as executable) include:
Burrows-Wheeler transform (BWT; block sorting pre-processing that makes compression more efficient)
LZ77 (used by Deflate)
LZW - Lempel-Ziv-Welch (Tiff image compression)
PPM There are three major types of lossy data compression technique. They are as follows:
Lossy transform codecs
Lossy predictive codecs
Chroma subsampling Thank you! original image
data compressed compressed original image
data restored data restored data lossless lossy JPG is optimized for photographs and similar continuous tone images that contain many, colours.
It can achieve great compression ratios even while maintaining very high image quality. GIF compression is unkind to such images. It uses lossy compression type.
JPG works by analyzing images and discarding kinds of information that the eye is least likely to notice. It stores information as 24 bit color.
The degree of compression of JPG is adjustable. At moderate compression levels of photographic images, it is very difficult for the eye to discern any difference from the original, even at extreme magnification. Compression factors of more than 20 are often quite acceptable.
Better graphics programs, such as Paint Shop Pro and Photoshop, allow you to view the image quality and file size as a function of compression level, so that you can conveniently choose the balance between quality and file size. Ivo Dimitrov, WDIT
Media Formats 2013 Chapman, C., 2010. Everything You Need to Know About Image Compression. [Online] Available at: [Accessed 10 Feb 2013].

Chastain, S., 2011. JPEG Myths and Facts. [Online] Available at: [Accessed 10 Feb 2013]., 2010. Theory of Data Compression. [Online] Available at: [Accessed 9 Feb 2013].

Kumar, S., 2001. An Introduction to Image Compression. [Online] Available at: [Accessed 10 February 2013].

Matthews, R., 2006. Digital Image File Types Explained. [Online] Available at: [Accessed 9 Feb 2013].

Ponomarenko, N., 2005. Cascade Fractal Image Compression and its Modification. Philadelphia, USA, International Conference on Acoustics, Speech and Signal Processing.

unknown, 2011. Maximum Compression. [Online] Available at: [Accessed 9 Feb 2013].

Zicara Ltd: online business solutions, 2011. Types of Lossy Compression. [Online] Available at: [Accessed 10 Feb 2013].
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