Compresión de imagen
Xulio Fernández Hermida
Curso 2005/2006
Fuentes de información
•	En esta presentación he utilizado información sacada de 
–	www.nationalarchives.gov.uk/
•	Ficheros 
–	graphic_file_formats.pdf y 
–	image_compression.pdf

Compresión de imagen
•	Consideraciones
–	Las imágenes pueden generar ficheros muy grandes
–	Que pueden ser comprimidos bastante sin una pérdida apreciable de calidad
–	Lo cual interesa a efectos de
•	almacenar y de
•	 transmitir por la red
–	Muchas técnicas de compresión son independientes del formato de fichero
Compresión de imagen 2
•	Factores a tener en cuenta
–	Eficiencia
–	Compresión con pérdidas (lossy) -para usar-
–	O sin pérdidas (lossless) -para almacenar-
–	Algoritmos abiertos -libres- o patentados
•	A tener en cuenta tanto en la creación 
•	Como en la disponibilidad a largo plazo
Compresión Run Length Encoding
–	El más simple. Sin pérdidas. Aplica a nivel de bits, bytes, pixels… (explicar)
–	Interesante en imágenes con grandes zonas planas
–	Hay diversas variantes y se usa en los formatos TIFF, PCX y BMP
Compresión LZ
–	En honor a sus autores Abraham Lempel y Jacob Ziv en 1977-78
–	El más conocido es el LZ77 que se usa en los algoritmos PKZIP y en la compresión de imagen del formato PNG
–	LZ78 se usa más en compresión de imagen
–	Y es la base del algoritmos LZW 
Compresión Huffman (explicar)
–	Desarrollado por David Huffman en 1952
–	Es uno de los algoritmos más antiguos y establecidos
–	Sin pérdidas
–	Se usa en muchos protocolos de transmisión de datos
–	Es una parte de la codificación JPEG y Deflate
Compresión Deflate 
–	Es un algoritmo de compresión sin pérdidas basado en LZ77 y codificación Huffman
–	Desarrollado por Phil Katz en 1996
–	Se usa en el algoritmo de compresión PKZIP y en la compresión de imagen del formato PNG
Compresión CCITT Grupo 3
–	Group3.- CCITT T4 was developed in 1985 
–	for encoding and  compressing 1-bit image data.
–	 Its primary use has been in fax  transmission.
–	it is optimised for scanned printed or handwritten documents. 
–	lossless algorithm, of which two forms exist: 
•	one-dimensional (which is a modified  version of Huffman encoding) and 
•	two-dimensional, which offers superior compression  rates. Due to its origin as a data transmission protocol, Group 3 encoding incorporates  error detection codes. 
Compresión CCITT Grupo 4
–	Group 4.- CCITT T.6 is a development of the two-dimensional  Group 3 standard, which is faster and offers compression rates which are typically double  those of Group 3. 
–	Like Group 3, it is lossless and designed for 1-bit images. 
–	However,  being designed as a storage rather than transmission format, it does not incorporate the  error detection and correction functions of Group 3 compression. 
Compresión LZW
–	by Terry Welch in 1984, as  a modification of the LZ78 compressor.
–	Lossless
–	can be  applied to almost any type of data.
–	most commonly used for image compression. 
–	effective on images with colour depths from 1-bit to  24-bit 
–	The patent for the LZW algorithm is owned by Unisys Corporation, which has licensed its  use in a variety of file formats, most notably CompuServe’s GIF format 
–	 It should be noted that the licensing applies to implementations of the LZW algorithm, and not to individual files which utilise it. 
–	The US  and the UK patent expired in 2004.    
–	LZW compression is encountered in a range of common graphics file formats, including  TIFF and GIF. 
Compresión: JPEG
•	1990. Colour and greyscale images.
•	JPEG is a lossy technique.
•	Best compression rates with  complex 24-bit (True Colour) images.
•	It discards image data  which is imperceptible to the human eye, using a technique called Discrete Cosine  Transform (DCT). 
•	It then applies Huffman encoding to achieve further compression.
•	JPEG comprises a baseline specification +optional extensions, including: 
–	Progressive JPEG. Useful for applications which need to stream image data. 
–	JPEG always involves some degree of lossy compression.
–	 Repeated saving  of an image lead to increasing degradation of the quality. 
•	Some questions of patent have expired in 2004. 
Compresión JPEG2000
•	JPEG 2000 is a replacement for the JPEG algorithm
–	lossy and lossless compression
–	wavelet compression 
–	 higher compression rates 
–	with a lower corresponding reduction in image quality.    
•	JPEG 2000 may utilise some patented technologies.
•	But intended to be made available  license- and royalty-free.    
•	Minimum file interchange format (JP2), 
–	in a similar  manner to JFIF and SPIFF. 
•	Support for JPEG 2000 is now beginning to appear in a  number of commercial software packages. 
Compresión PNG
•	PNG compression was developed in 1996 
–	as part of the PNG file format. 
•	PNG compression uses the Deflate compression  method. 
•	It is a lossless algorithm and is effective with colour depths from 1-bit to 48-bit.
•	Unencumbered by patent and free to use. 
•	It is implemented only in  the PNG file format.
•	 It is a W3C recommendation.  
•	Version 1.2 is intended to be released as an ISO standard 
Compresión fractal 1
•	Fractal compression uses the mathematical principles of fractal geometry to identify  redundant repeating patterns within images. 
•	These matching patterns may be identified  through performing geometrical transformations, such as scaling and rotating, on  elements of the image. 
•	Once identified, a repeating pattern need only be stored once,  together with the information on its locations within the image and the required  transformations in each case.
•	 Fractal compression is extremely computationally intensive,  although decompression is much faster. 
Compresión fractal 2
•	It is a lossy technique, which can achieve large  compression rates. 
•	Unlike other lossy methods, higher compression does not result in pixelation of the image and, although information is still lost, this tends to be less  noticeable. 
•	Fractal compression works best with complex images and high colour depths.    
•	The original fractal compression algorithm was developed by Michael Barnsley in 1991.  
•	However, the algorithm is patented and supported by few commercial products. 
•	It is not  implemented in any common graphics file formats.
Conclusión
•	Algorithm  Lossiness  Efficient with  
•	RLE  Lossless  Monochrome or images with large blocks of colour  
•	LZ Compressors  Lossless  All images  
•	Huffman Encoding  Lossless  All images  
•	Deflate  Lossless  All images  
•	CCITT Group 3 & 4  Lossless  Monochrome images  
•	LZW  Lossless  All images  
•	JPEG  Lossy (lossless extension available)  Complex, True Colour images  
•	JPEG 2000  Lossy, lossless supported  Complex, True Colour images  
•	PNG  Lossless  All images  
•	Fractal  Lossy  Complex, True Colour images