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Image Compression

Image Compression. Forms of data - text, numerical, image, video contain redundant elements. Data can be compressed by eliminating the redundant elements. A code is substituted for the eliminated redundant element, where the code is shorter than eliminated element.

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Image Compression

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  1. Image Compression

  2. Forms of data - text, numerical, image, video contain redundant elements. • Data can be compressed by eliminating the redundant elements. • A code is substituted for the eliminated redundant element, where the code is shorter than eliminated element. • When compressed data is retrieved from storage or received over a communications link, it is expanded back to its original form, based on the code. • Compression is used: • to save storage space • to reduce communications transmission requirements • Digital realm: using lesser number of bits to represent information

  3. REDUNDANCY Most types of computer files are fairly redundant they have the same information listed over and over again. File-compression programs simply get rid of the redundancy “Ask not what your country can do for you -- ask what you can do for your country.”

  4. Techniques • Lossless • Data can be completely recovered after decompression • Recovered data is identical to original • Exploits redundancy in data • Lossy • Data cannot be completely recovered after decompression • Some information is lost for ever • Gives more compression than lossless • Discards “insignificant” data components

  5. Image Compression • Image compression can be lossy or lossless • Methods for lossless image compression are: • Run-length encoding • Entropy coding • Adaptive dictionary algorithms such as LZW • Methods for lossy compression are: • Reducing the color space to the most common colors in the image. The selected colors are specified in the color palette in the header of the compressed image. Each pixel just references the index of a color in the color palette. This method can be combined with dithering to blur the color borders. • Transform coding. This is the most commonly used method. A Fourier-related transform such as DCT or the wavelet transform are applied, followed by quantization and entropy coding. • Fractal compression.

  6. JPEG • JPEG is named after its origin, the Joint Photographers Experts Group • This involves reducing the number of bits per sample or entirely discard some of the samples

  7. MULTIMEDIA COMPRESSION • Multimedia compression is a general term referring to the compression of any type of multimedia, most notably graphics, audio, and video • MPEG (Moving Pictures Experts Group ) The future of this technology is to encode the compression and uncompression algorithms directly into integrated circuits. • The approach used by MPEG can be divided into two types of compression: within-the-frame and between-frame

  8. DATA COMPRESSION ALGORITHMS LOSS LESS COMPRESSION Run Length Encoding Huffman Coding LZW LOSSY COMPRESSION JPEG MPEG

  9. RUN-LENGTH ENCODING Data files frequently contain the same character repeated many times in a row. Example of run-length encoding. Each run of zeros is replaced by two characters in the compressed file: a zero to indicate that compression is occurring, followed by the number of zeros in the run.

  10. Run Length Encoding CTAAAAAGGGTCGTTTTTTGCCCGGGGGCCTCCCCCCC CTAAAAAGGGTCGTTTTTTGCCCGGGGGCCTCCCCCCC CTAAAAAGGGTCGTTTTTTGCCCGGGGGCCTCCCCCCC CT5A3GTCG6TG3C5GCCT7C } Run length encoded: 21 symbols

  11. Run Length Encoding (cont.) WWWBWWWWWBWWWBWWWWBWWWWWBWWWBWWWWWBWWBWWWWWWBBBWWWWWWWBWBWWWWWWWBWWBBWWWWWBWWWWBWWWWBWWWWB WWWBWWWWWBWWWBWWWWB…. 3WB5WB3WB4WB…. 3151314 possible optimization, but… #W3151314….. Optimization requires escape character

  12. HUFFMAN ENCODING This method is named after D.A. Huffman, who developed the procedure in the 1950s. More than 96% of this file consists of only 31 characters out of 127

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