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1 Vladimir Botchko [email protected] Lecture 6. Image Lecture 6. Image Compression Compression Lappeenranta University of Technology (Finland)
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1 Vladimir Botchko [email protected] Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

Dec 21, 2015

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Page 1: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Vladimir Botchko [email protected]

Lecture 6. Image CompressionLecture 6. Image Compression

Lappeenranta University of Technology (Finland)

Page 2: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Image CompressionImage Compression

Lossy and lossless compression Fundamentals Fidelity Criteria Image Compression Models Error Free Compression Lossy Compression Compression Standards Video Image Compression

Page 3: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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FundamentalsFundamentals

Coding redundancy Interpixel Redundancy Psychovisual Redundancy

Page 4: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Image CompressionImage Compression

Lossy and lossless compression Fundamentals Fidelity Criteria Image Compression Models Error Free Compression Lossy Compression

Page 5: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Image CompressionImage Compression

Lossy and lossless compression Fundamentals Fidelity Criteria Image Compression Models Error Free Compression Lossy Compression

Page 6: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Error Free CompressionError Free Compression

Variable-length coding Huffman coding Near optimal variable length codes Lossless predictive coding

Page 7: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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One-dimensional predictive coding

Right histogram is a Laplacian pdf

Page 8: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Image CompressionImage Compression

Lossy and lossless compression Fundamentals Fidelity Criteria Image Compression Models Error Free Compression Lossy Compression

Page 9: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Lossy CompressionLossy Compression

Delta Modulation DM Differential pulse code modulation DPCM Transform coding

Page 10: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Lossy CompressionLossy Compression

Delta Modulation DM Differential pulse code modulation DPCM Transform coding

Page 11: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Transform CodingTransform Coding

Transform basis functions Fourier transform Walsh-Hadamard transform Discrete cosine transform Wavelet transform

Page 12: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Transform CodingTransform Coding

ON-LINE DEMO on the course Web page (browser with Java 2): References: Dmitry Kolesnikov: Introduction Lecture

Page 13: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Walsh-Hadamard transform

Walsh-Hadamard basis images: one – black, minus one – white.

Page 14: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Transform CodingTransform Coding

Transform basis functions Fourier transform FT Walsh-Hadamard transform WHT Discrete cosine transform DCT Wavelet transform WT

Page 15: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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DCT

Image udersampling (upper row), DCT (lower row)

Page 16: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Transform CodingTransform Coding

Transform basis functions Fourier transform Walsh-Hadamard transform Discrete cosine transform Wavelet transform

Page 17: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Haar transform

Haar basis images: positive-black, negative-white, zero-gray

Page 18: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Wavelet Transform (1 level decomposition)

Page 19: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Wavelet Transform (2 level decomposition)

Page 20: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Wavelet transform

Wavelets (upper row), image undersampling (lower row), compare with DCT

Page 21: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Image CompressionImage Compression

Lossy and lossless compression Fundamentals Fidelity Criteria Image Compression Models Error Free Compression Lossy Compression Compression Standards Video image compression

Page 22: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Video image compression

A moving image sequence 192 kB/frame (left), intra (independetly inside frame) frame compression 6 kB/frame (center), inter (by subtraction of frames) frame compression 512 bytes/frame and intra compression is also kept (right).

MPEG format.

Page 23: 1 Vladimir Botchko botchko@lut.fi Lecture 6. Image Compression Lappeenranta University of Technology (Finland)

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Gray-scale image compression. Fractals.

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