Medical Image Compression
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Transcript of 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