variable metric for binary vector quantization university of joensuu department of computer science...

14
Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Upload: ezequiel-poplin

Post on 31-Mar-2015

223 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Variable Metric For Binary Vector Quantization

UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCEJOENSUU, FINLAND

Ismo Kärkkäinen and Pasi Fränti

Page 2: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Distance and distortion functions

Distance function:

Distortion function:

dK

k

d

jkikjid cxcxL

1

1

,

N

ipidN i

cxLCXE1

1 ,,

Page 3: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Distortion for binary data

Internal distortion for one variable:

djkjkdjkjkjk crcqD 1

qjk = the number of zeroes rjk = the number of onesCjk = the current centroid value for

variable k of group j.

Page 4: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Optimal centroid positionOptimal centroid position depends on the metric. Given:

1/1 dThe optimal position is:

jkjk

jkjk

rq

rc

Page 5: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Proposed algorithm

Create initial solution. Set d to dmax. While d > dmin, do: Perform one GLA iteration. Decrease d. Set d to dmin. Iterate GLA until solution has converged. Return final solution.

Page 6: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Example of centroid location

0.50

0.60

0.70

0.80

0.90

1.00

6.0 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0

d

c

q=10,r=90

q=20,r=80

q=30,r=70

q=40,r=60

Page 7: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Second example

q = 7 5 r = 2 50 .0 1 .0

c = 0 .5

c = 0 .3 7

c = 0 .2 5

c = 0

d = ( = 0 )

d = 3 ( = 0 .5 )

d = 2 ( = 1 )

d = 1

Page 8: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Test images

Blockwise quantization of pixels into two levels according to the mean value of the 4x4 blocks.

44 pixel blocks.

Page 9: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Results for Bridge

Bridge1

.48

9

1.4

67

1.3

87

1.4

41

1.3

86

1.2

93

1.3

67

1.3

32

1.3

08

1.2

45

1.1

1.2

1.3

1.4

1.5

1.6

GLA SA Split PNN

Dis

tort

ion

Binary

Soft

Prop.

Page 10: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Results for Camera

Camera1

.77

1

1.7

65

1.6

74

1.6

93

1.6

46

1.5

45

1.6

59

1.6

01

1.5

56

1.4

96

1.4

1.5

1.6

1.7

1.8

GLA SA Split PNN

Dis

tort

ion

Binary

Soft

Prop.

Page 11: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Results for CCITT-5

CCITT-5

0.0

33

0.0

40

0.1

37

0.0

26

0.0

31

0.0

29

0.1

65

0.0

26

0.0

45

0.0

27

0.00

0.05

0.10

0.15

0.20

GLA SA Split PNN

Dis

tort

ion

Binary

Soft

Prop.

Page 12: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Results for DNA

DNA7

.05

6

6.6

22

6.5

74

7.2

30

6.7

57

6.6

62

6.5

96

6.5

70

6.6

27

6.5

70

6.2

6.4

6.6

6.8

7.0

7.2

7.4

GLA SA Split PNN

Dis

tort

ion

Binary

Soft

Prop.

Page 13: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Different parameter combinations (Bridge)

GLA SA

Linear Exponential Exponential

d0 0.05 0.1 0.25 0.95 0.99 0.95 0.99 2 1.325 1.335 1.359 1.318 1.314 1.278 1.254 3 1.319 1.327 1.346 1.312 1.310 1.269 1.245 4 1.318 1.325 1.344 1.310 1.309 1.268 1.246 5 1.317 1.324 1.344 1.311 1.309 1.270 1.249 6 1.318 1.323 1.342 1.311 1.307 1.271 1.252

Page 14: Variable Metric For Binary Vector Quantization UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND Ismo Kärkkäinen and Pasi Fränti

Different parameter combinations (DNA)

GLA SA Linear Exponential Exponential

d0 0.05 0.1 0.25 0.95 0.99 0.95 0.99 2 6.679 6.718 6.728 6.646 6.668 6.571 6.571 3 6.646 6.688 6.701 6.628 6.641 6.570 6.570 4 6.685 6.644 6.647 6.643 6.641 6.570 6.570 5 6.662 6.661 6.671 6.630 6.627 6.570 6.570 6 6.663 6.643 6.659 6.637 6.682 6.570 6.570