Medical Image Compression

Medical

Image Compression

Digital Signal Processing

Digital Image Processing

Image CompressionMedical Image Compression

Medical Image Compression

Joint Photographic Experts Group

Region Of Interest

Embedded Zerotree Wavelet

Unit Embedded Zerotree Wavelet

Algorithms Used

DCT

DWT

1 Joint Photographic Experts Group

o Introductiono Discrete Cosine

Transformationo Algorithmo Compression Results

Joint Photographic Experts GroupIntroduction

Based on discrete cosine transformation

Lossy compression method

Mostly used by digital cameras and web usage

Bitmap Image, 150KB

JPEG Compressed, 14KB

Joint Photographic Experts GroupDiscrete Cosine Transformation

Time Domain Frequency Domain

DCT is a time to frequency domain transformation.

Joint Photographic Experts GroupAlgorithm

8x8 pixelblocks

DCTQuantization

Zig-zag scan

RLE

HuffmanEncoding

Quantization Table

Output

Quantization results in loss of information .

Compressed output is losslessly stored .

Joint Photographic Experts GroupCompression Results

Lena

X-Ray MRI0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.10

50

100

150

200

250

MSE

LenaX-RayMRI

Bitrate

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.105

1015202530354045

PSNR

LenaX-RayMRI

Bitrate

2 Region Of Interest

o Introductiono Compression Resultso Comparison with JPEG

Region Of InterestIntroduction

Original Image ROI

Portion of image containing the significant information is selected as ROI and compressed at a higher quality .

Region Of InterestCompression Results

X-Ray MRI 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80

20

40

60

80

100

120

140

MSE

X-rayMRICAT Scan

Bitrate

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80

10

20

30

40

50

PSNR

X-rayMRICAT Scan

Bitrate

CAT Scan

Region Of InterestComparison with JPEG

0.10.20.30.40.50.60.70.80.9 1 1.10

50

100

150

200

250

0.10.20.30.40.50.60.70.80.9 1 1.105

10152025303540

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90

20

40

60

80

100

120

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.905

1015202530354045

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90

20

40

60

80

100

120

140

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.905

1015202530354045

MSE

PSNR

X-Ray MRI CATScan

ROI

JPEG

3 Embedded Zerotree Waveleto Introductiono Discrete Wavelet

Transformationo Zerotree Concepto An Example

Embedded Zerotree WaveletIntroduction

Embedded – The EZW encoder is based on progressive encoding. Progressive encoding is also known as embedded encoding.

Zerotree – A data structure called zero-tree is used in EZW algorithm to encode the data.

Wavelet – The EZW encoder is specially designed to work with wavelet transform. It was originally designed to operate on images.

Embedded Zerotree WaveletDiscrete Wavelet Transformation

OriginalImage

FirstLevel

SecondLevel

ThirdLevel

Lower sub-band has higher resolution and contains higher frequency information.

Embedded Zerotree WaveletZerotree Concept

A zerotree is a quad-tree having all its descendents less than the current threshold.

Quad-treeStructure

An Example

Embedded Zerotree WaveletAn Example

63P

-34N

49P

10T

7Z

13Z

-12 7

-31Z

23T

14T

-13T

3Z

4Z

6 -1

15T

14Z

3 -12 5 -7 3 9

-9T

-7T

-14 8 4 -2 3 2

-5 9 -1Z

47P

4 6 -2 2

3 0 -3Z

2Z

3 -2 0 4

2 -3 6 -4 3 6 3 6

5 11 5 6 0 3 -4 4

Dominant Pass 1

Threshold = 32 Output = PNZTPTTTTZTTZZZZZPZZ

Subordinate Pass 1

List = {63 34 49 47 } Output = 1 0 1 0

4 Unit Embedded Zerotree Wavelet *

o Drawback of existing algorithm

o Concept of Unit Cello Formation of Unit Cello Comparison with existing

algorithm

* Paper under Review process

Unit Embedded Zerotree Wavelet *Drawback of existing algorithm

Dimensions

Children Descendents

8 x 8 284 378

32 x 32 6,859 8,564

128 x 128 1,10,576 1,36,407

256 x 256 4,43,492 5,67,959

Existing algorithm needs to check a large number of children and descendents.

* Paper under Review process

Unit Embedded Zerotree Wavelet *Concept of Unit Cell

Smallest possible square matrix generated from the wavelet decomposed image, having the same level of wavelet

decomposition structure as the original image.

* Paper under Review process

n

n

2

2

Unit Embedded Zerotree Wavelet *Formation of Unit Cell

Smallest possible square matrix generated from the wavelet decomposed image, having the same level of wavelet

decomposition structure as the original image.

* Paper under Review process

Decomposition

Level

Unit Cell Order

1 2

2 4

3 8

n 2n

Unit Embedded Zerotree Wavelet *Comparison to Existing Algorithm

* Paper under Review process

Image

Original algorithm Proposed algorithm

32×32

64×64

128×128

256×256

32×32

64×64

128×128

256×256

LENA 1.092 4.540 20.062 210.617 0.952 3.479 13.120 52.073

BARBARA 1.108 4.477 19.407 213.425 0.983 3.572 13.915 54.632

CAMRAMAN 1.139 4.618 20.639 200.960 0.998 3.588 13.463 53.867

GOLDHILL 1.136 4.680 20.779 216.670 0.996 3.510 13.541 54.226

PEPPERS 1.186 4.524 19.812 214.626 1.030 3.650 14.258 54.632

Table showing coding time (seconds) for original and proposed algorithm.

Unit Embedded Zerotree Wavelet *Comparison to Existing Algorithm

* Paper under Review process

Table showing percentage improvement in coding time using proposed algorithm over original algorithm.

Image

Percent

32×32

64×64

128×128

256×256

LENA 12.821 23.370 34.603 75.276

BARBARA 11.282 20.214 28.299 74.402

CAMRAMAN 12.379 22.304 34.769 73.195

GOLDHILL 12.324 25.000 34.833 74.973

PEPPERS 13.153 19.319 28.034 74.545

01020304050607080

Percent

32 × 32 64 × 64 128 × 128 256 × 256

Image Dimensions (pixels)

LENA BARBARA CAMRAMAN GOLDHILL PEPPERS