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Section 3. Image Compression

Xudong Ni

Group Member: Wei Yan,Li Yang,Xudong Ni

Computer Science Florida International University

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Outline Classification of Image Compression Methods Object Quality Measure The principles of image compression Lossless compression techniques

Huffman coding Arithmetic coding

Lossy compression techniques Subband/Wavelet Coding (Examples)

Overview of JPEG 2000 (Examples) Overview of MPEG

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Classification of Image Compression Methods

Still image compression Lossless compression techniques

Huffman coding Arithmetic coding

Lossy compression techniques Scalar quantization:

Discrete Cosine Transform(DCT) etc. Transform coding:

Differential Pulse coding modulation(DPCM) etc. Subband/Wavelet Coding

Motion picture compression MPEG etc.

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Object Quality Measure Fidelity judgment

Mean Square Error(MSE)

Peak Signal-to-Noise Ratio (PSNR)

The smaller the MSE, the higher the PSNR, the better image

quality.

Subjective criteria/Visual qualityFive point scales: bad, poor, fair, good,

excellent

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The principles of image compression Redundancy reduction

exploit the properties of the signal sources, e.g., the statistical property, and to remove redundancy from the signal

Irrelevancy reduction exploit the properties of the signal receiver

(usually the human visual system) and to remove parts or details of the signal that will not be noticed by the receiver.

Most methods exploit both of them

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Huffman code Basic ideal:

The idea behind Huffman coding is simply to use shorter bit patterns for more common characters, and longer bit patterns for less common characters

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Arithmetic coding Basic ideal

While Huffman coding gives a way of rounding the code words to close integer values and constructing a code with those lengths, arithmetic coding actually manages to encode symbols using non-integer numbers of bits.

It can produce 5-10% better than compression than Huffman coding

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Overview of JPEG(DCT based)

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Subband/Wavelet Coding Basic idea

divide the frequency band of the signal and then to code each subband with either PCM or DPCM using a coder and bit rate accurately matched to the statistic of that band.

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Subband Filtering and Decomposing

Filter bank with morphological filter yielding perfect reconstruction

M(x) is a generalized half-band filter

x

I-M(x)

M(x)

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“Lena” two subband

Original “Lena” image Two subband decomposing

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Seven subband decomposing

Seven subband decomposing using Morphological Subband Decomposition(MSD)

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Advantage of Subband coding It supplies a scalable image

representation method and facilitates progressive transmission

It has good subjective error properties

It has good performance

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Overview of JPEG 2000 major change from the current JPEG is

that wavelets will replace DCT as the means of transform coding

Features it addresses Low bit-rate compression performance Lossless and lossy compression in a single

codestream Transmission in noisy environment where bit-

error is high Interface with MPEG-4 Content-based description

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Example1 of JPEG2000JPEG2000 image (middle) shows almost no quality loss from current JPEG, even at 158:1 compression.

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Example2 of JPEG2000

Original image Current JPEG JPEG2000

The compression rate of current JPEG and JPEG 2000 is 99.30%

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Overview of MPEG MPEG-1: the standard on which such products

as Video CD and MP3 are based MPEG-2: Digital Television set top boxes and

DVD are based MPEG-4: the standard for multimedia for the

web and mobility MPEG-7: Multimedia Content Description

Interface(scheduled for July 2001 )

MPEG-21: Multimedia Framework (started in June 2000 )