En Jpeg Comp

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JPEG – 2000 COMPRESSION

JPEG – 2000 COMPRESSION Presented By

SOURYA PRAKASH PARIDA Roll no. EI 2001 17 202 Under the guidance of

DR. SAROJ KUMAR MEHER SOURYA PRAKASH PARIDA

[1]

JPEG – 2000 COMPRESSION

Need for image compression Sufficient storage space. Lesser transmission time. Large transmission bandwidth. After transmission, the images can be decompressed at the receiver when required.

A compression ratio of N:1 reduces the space & transmission time by a factor of N as well as increases the transmission bandwidth by the same factor. SOURYA PRAKASH PARIDA

[2]

JPEG – 2000 COMPRESSION

Principles behind compression Types of Redundancy:

Spatial Redundancy Spectral Redundancy Temporal Redundancy Fundamental Components of Compression:

Redundancy Reduction Irrelevancy Reduction

SOURYA PRAKASH PARIDA

[3]

JPEG – 2000 COMPRESSION

Classification of compression Loss-less vs. Lossy Compression Loss-less: Digitally identical image after compression. Lossy: Greater image compression with blurred image output.

Predictive vs. Transform Coding Predictive: Information already received is used to predict future values. Transform: Signal is transformed from spatial domain to other space using a well-known transform.

Sub-band Coding The frequency band of a signal is split into various subbands, using octave tree decomposition of the image. SOURYA PRAKASH PARIDA

[4]

JPEG – 2000 COMPRESSION

Image compression system

Source Encoder: Transforms the signal from the spatial domain to a well-known transform/domain.

Quantizer: Reduces the no. of bits needed to store the transformed coeff. by reducing the precision of those values.

Entropy Encoder: Further compresses the quantized values without any loss to give better overall compression. SOURYA PRAKASH PARIDA

[5]

JPEG – 2000 COMPRESSION

DCT - based compression system

DCT- based JPEG Encoder Block Diagram

DCT- based JPEG Decoder Block Diagram SOURYA PRAKASH PARIDA

[6]

JPEG – 2000 COMPRESSION

Disadvantages of DCT Undesirable blocking artifacts affect the reconstructed images or video frames.

Impossible to completely decorrelate the blocks at their boundaries using DCT.

Not efficient for binary image (fax or pictures of fingerprints) characterized by large periods of constant amplitude, followed by brief periods of sharp transitions. SOURYA PRAKASH PARIDA

[7]

JPEG – 2000 COMPRESSION

Discrete Wavelet Transform (DWT) Wavelet transform decomposes a signal into a set of basis functions called wavelets.

SOURYA PRAKASH PARIDA

[8]

JPEG – 2000 COMPRESSION

Advantages of DWT over DCT It provides higher compression ratios & avoids blocking artifacts.

Allows good localization both in spatial & frequency domain.

Transformation of the whole image introduces inherent scaling.

Better identification of which data is relevant to human perception higher compression ratio. SOURYA PRAKASH PARIDA

[9]

JPEG – 2000 COMPRESSION

JPEG – 2000 Algorithm Division of the image into rectangular, non-overlapping tiles.

Tiling of components with different sub-sampling factors w.r.t. a high-resolution grid.

Maintaining the size of each tile to be the same, with the exception of tiles around the border (all four sides) of the image.

Conversion of the input series into high-pass & low-pass wavelet coefficient series (of length n/2 each) using DWT. SOURYA PRAKASH PARIDA

[10]

JPEG – 2000 COMPRESSION

JPEG – 2000 Algorithm (contd.) The high-pass & low-pass wavelet coeff. series are given by:

k −1

H = ∑x i

m =0

2 i −m

k −1

L = ∑x i

m =0

SOURYA PRAKASH PARIDA

2 i −m

.s ( z ) m

.t ( z ) m

[11]

JPEG – 2000 COMPRESSION

JPEG – 2000 Algorithm (contd.) Uniform scalar quantization of the wavelet coeff. employing a fixed dead-zone about the origin.

Division of the magnitude of each coeff. by a quantization step size and rounding down.

Division of each sub-band into regular non-overlapping rectangles by “packet partition”.

Three spatially consistent rectangles (one from each sub-band) comprise a packet partition location.

Code-blocks obtained by dividing each packet partition location into regular non-overlapping rectangles. SOURYA PRAKASH PARIDA

[12]

JPEG – 2000 COMPRESSION

JPEG – 2000 Algorithm (contd.) Entropy coding carried out as context-dependent, binary, arithmetic coding of bitplanes.

Collection of each code-block in a packet partition location to form the body of a “packet.”

SOURYA PRAKASH PARIDA

[13]

JPEG – 2000 COMPRESSION

Visual Comparison

Original Bitmap Image

JPEG (DCT) Image

JPEG-2000 (DWT) Image

(43:1 compression ratio)

(43:1 compression ratio)

The DWT-based JPEG-2000 image compression has a rate-distortion advantage over the original JPEG. SOURYA PRAKASH PARIDA

[14]

JPEG – 2000 COMPRESSION

Conclusion JPEG – 2000 Provides

Protective image security. Improved low bit-rate compression performance. Transmission in noisy environments. Progressive transmission by pixel accuracy and resolution.

Improved continuous-tone and bi-level compression of larger images. SOURYA PRAKASH PARIDA

[15]

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