Digital watermarking techniques for JPEG2000 scalable image coding

Transcription

1 Electronic & Electrical Engineering. Communications Research Group. Digital watermarking techniques for JPEG2000 scalable image coding Deepayan Bhowmik The University of Sheffield, Sheffield, UK

2 Contents Introduction Digital watermarking: properties and applications Discrete wavelet transform and its applications Scalable image coding and its application in multimedia signal processing Research techniques for image watermarking for JPEG2000 content adaptation Recent developments and open questions in this field

3 Contents Introduction Digital watermarking: properties and applications Discrete wavelet transform and its applications Scalable image coding and its application in multimedia signal processing Research techniques for image watermarking for JPEG2000 content adaptation Recent developments and open questions in this field

4 Introduction A digital watermark is the copyright or author identification information which is embedded directly in the digital media in such a way that it is imperceptible, robust and secure. Audio watermarking Image watermarking Video watermarking

5 Digital watermarking: properties and applications + =

6

7 Example

8 Example

9 Example

10 Digital watermarking : properties Imperceptibility Measurement metrics: RMSE, PSR, SSIM etc.

11 Digital watermarking : properties Imperceptibility Measurement metrics: RMSE, PSR, SSIM etc. Robustness Measurement metric: Hamming distance, Correlation etc.

12 Digital watermarking : properties Imperceptibility Measurement metrics: RMSE, PSR, SSIM etc. Robustness Measurement metric: Hamming distance, Correlation etc. Fragility Tamper-resistance Data payload

13 Applications Copyright protection. Owner identification. Content authentication. Broadcast monitoring. Transaction tracking. Media digital rights management (DRM) in content supply chain. Tamper proofing.

14 Contents Introduction Digital watermarking: properties and applications Discrete wavelet transform and its applications Scalable image coding and its application in multimedia signal processing Research techniques for image watermarking for JPEG2000 content adaptation Recent developments and open questions in this field

15 Discrete Wavelet Transform (DWT) and applications

16 DWT I G 0 G H L G 0 G 1 G 0 G HH HL LH LL 2D wavelet decomposition

17 DWT LL2 HL2 HL1 LH2 HH2 LH1 HH1 2 level decomposition

18 DWT Applications Compression JPEG-2000 image compression MC-EZBC video compression De-noising Edge-detection Image retrieval Gait analysis Digital communication and many others

19 Contents Introduction Digital watermarking: properties and applications Discrete wavelet transform and its applications Scalable image coding and its application in multimedia signal processing Research techniques for image watermarking for JPEG2000 content adaptation Recent developments and open questions in this field

20 Scalable image coding

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22 JPEG2000 image coding using DWT

23 JPEG2000

24 JPEG2000 image coding

25 Bit plane JPEG2000 image coding LH1 LH2 LL2 HH2 HL2 HH1 1 HL1 Most significant Bit plane -1 0 Bit plane -2 1 LH2 LL2 HH2 HL2 HL1 Least significant Bit plane 0 LH1 HH1 0

26 JPEG2000 image coding Quarter Resolution LL2 LH2 HL2 HH2 Half Resolution LL1 HL1 Full Resolution LH1 HH1

27 Resolution scalability

28 Resolution scalability

29 Resolution scalability

30 Quality scalability

31 Quality scalability

32 Quality scalability

33 Example

34 Contents Introduction Digital watermarking: properties and applications Discrete wavelet transform and its applications Scalable image coding and its application in multimedia signal processing Research techniques for image watermarking for JPEG2000 content adaptation Recent developments and open questions in this field

35 Robust watermarking techniques for scalable coding

36 Watermarking techniques Original Image (I) Watermark (W ) Embedding () Watermarked Image (I') Test Image (I') Extraction () Extracted watermark (W ') Authentication Watermark detection decision Original Image (for non-blind type) (I) Original watermark (W )

37 Watermarking techniques Embedding Domain Pixel Domain Transform Domain Fourier DCT Wavelet on-blind Blind

38 Watermarking techniques Host Image DWT Coefficient selection and watermark embedding IDWT Watermarked Image Attack including content adaptation Watermark Test image Authentication Decision Comparison of original and extracted watermark Extracted Watermark Watermark Extraction (Blind / on-blind) DWT

39 Watermarking techniques C ' m, n Embedding C C m w m, n, n m, n, Extract C' C w ext C, where C m,n = modified coefficient, C m,n = wavelet coefficient to be modified, w m,n = watermark information, α = watermark strength parameter, w ext = extracted watermark.

40 C q Wavelet based image compression (Bit-plane discarding): C Q, where C q = quantised coefficient, C = original coefficient, Q = quantisation parameter, Cˆ Q. C q Q 1 2, Cˆ = decoded coefficient Q = 2 k ±1, ±2, ±3 C k = Center point value ( k 1). 2 k. 2 ( k 1). 2 C k ( k ( 1) 1) C k k C IET/IPR 2012 The University of Sheffield, UK

41 Algorithm 1: Embed 1: C & C in different cluster: k.2 C k.2. 1 w 1 w 1 = value to embed 1. ( k 1). 2 k. 2 ( k 1). 2 C( k 1) C k C' C k.2 1 w 1

42 Robustness Analysis : Embed 1: C & C in same cluster: k.2 Ck C. 1 T T = Threshold for watermark detection. ( k 1). 2 k. 2 ( k 1). 2 C( k 1) Ck C' C C k T 1

43 Robustness Analysis : Embed 1: combined: k.2 Ck C 1 w1 1 T. ( k 1). 2 k. 2 ( k 1). 2 C( k 1) C k C' C k.2 1 w 1 C k 1 T

44 Robustness Analysis : Embed 0: C & C in different cluster: k.2 1 w 0 C k.2. w 0 = value to embed 0. ( k 1). 2 k. 2 ( k 1). 2 C( k 1) k.2 1 w 0 Ck C' C

45 Robustness Analysis : Embed 0: C & C in different cluster: C ( k 1) k.2 C. 1 T 1 w0 ( k 1). 2 k. 2 ( k 1). 2 C' C( k 1) 1 T C( k 1) k.2 1 w 0 Ck C

46 Robustness Analysis : Embed 1 or 0 for correct watermark extraction: k.2 k.2 C 1 w 1 1 w 0. ( k 1). 2 k. 2 ( k 1). 2 C( k 1) 1 T C( k 1) C k C k.2 1 w 1 k.2 1 w 0 C k T 1

47 Simulation results : Map of original coefficient values (C) to retain the watermark information.

48 Hamming Distance Simulation results : Effect of coefficient selection on JPEG2000 compression for different. CR = 64: Image 1 Image 2 Image 3 Image 4 Image 5 Image Effect of bit-plane based coefficient selection procedure against JPEG2000 quality scaling considering 64:1 compression ratio. Quantisation steps: Q = 2 0 to Q = 2 9.

49 C q Wavelet based image compression (Bit-plane discarding): C Q, where C q = quantised coefficient, C = original coefficient, Q = quantisation parameter, Cˆ Q. C q Q 1 2, Cˆ = decoded coefficient Q = 2 k ±1, ±2, ±3 C k = Center point value ( k 1). 2 k. 2 ( k 1). 2 C k ( k ( 1) 1) C k k C IET/IPR 2012 The University of Sheffield, UK

50 Algorithm 2: ( n 1)%2 n% C ( n 1) (n) ( n 1) 0 C 1 2( n) / 2 ( 2n 1) / 2 2( n 1) / 2 M C 4( n) / 4 ( 4n 1) / 4 2(2n 1) / 4 0 C 1 2(4n 1) /8 ( 8n 3) /8 4(2n 1) / 8 IET/IPR 2012 The University of Sheffield, UK

51 Embedding algorithm n% Tree depth d Tree for C: b( C) ( n%2) b i C 2 i %2, i 0,1,2,3..., C b( C) d 6 IET/IPR 2012 The University of Sheffield, UK

52 Tree based watermarking rule Symbols Binary Tree Watermark association Embedded Zero (EZ) 000xxxx 0 Embedded Zero (EZ) 001xxxx 0 Cumulative Zero (CZ) 010xxxx 0 Weak One (WO) 011xxxx 1 Weak Zero (WZ) 100xxxx 0 Cumulative One (CO) 101xxxx 1 Embedded One (EO) 110xxxx 1 Embedded One (EO) 111xxxx 1 IET/IPR 2012 The University of Sheffield, UK

53 Experimental Results Existing Algorithm Proposed Algorithm PSR Data capacity (L) PSR Data capacity (L) Boat (704x576) Barbara (704x576) Blackboard (704x576) Light House (768x512)

54 Experimental Results Hamming Distance Hamming Distance Robustness against bit plane discarding: Blackboard d=5 ( =31) 0.5 d=5 ( =329) d=6 ( =112) d=6 ( =1278) 0.4 d=7 ( =466) d=7 ( =4980) p Robustness against JPEG2000: Blackboard d=5 ( =31) d=5 ( =329) d=6 ( =112) d=6 ( =1278) d=7 ( =466) d=7 ( =4980) IET/IPR 2012 The University of Sheffield, UK JPEG2000 compression Ratio

55 Experimental Results Hamming Distance Hamming Distance Robustness against bit plane discarding: Light House d=5 ( =31) 0.5 d=5 ( =335) d=6 ( =125) d=6 ( =1358) 0.4 d=7 ( =482) d=7 ( =5129) p Robustness against JPEG2000: Light House d=5 ( =31) d=5 ( =335) d=6 ( =125) d=6 ( =1358) d=7 ( =482) d=7 ( =5129) IET/IPR 2012 The University of Sheffield, UK JPEG2000 compression Ratio

56 Experimental Results Hamming Distance Hamming Distance 0.3 Robustness against JPEG2000: Blackboard Proposed algorithm Existing algorithm JPEG2000 compression Ratio 0.25 Robustness against JPEG2000: Light House Proposed algorithm Existing algorithm IET/IPR 2012 The University of Sheffield, UK JPEG2000 compression Ratio

57 Experimental Results Hamming Distance Hamming Distance 0.3 Robustness against JPEG2000: Blackboard Proposed algorithm Existing algorithm JPEG2000 compression Ratio 0.25 Robustness against JPEG2000: Light House Proposed algorithm Existing algorithm IET/IPR 2012 The University of Sheffield, UK JPEG2000 compression Ratio

58 Contents Introduction Digital watermarking: properties and applications Discrete wavelet transform and its applications Scalable image coding and its application in multimedia signal processing Research techniques for image watermarking for JPEG2000 content adaptation Recent developments and open questions in this field

59 Demo Watermarking demo.

60 Open questions in this field and comments Watermarking a growing research area for digital copyright protection and other applications. Scalable coded contents are being used for various applications including mobiles. Watermarking for scalable coded contents are challenging and needs more research. Video watermarking is a promising research area to explore.

61 Pointers WEBCAM Framework developed by The University of Sheffield.

62 Pointers

63 Electronic & Electrical Engineering. Communications Research Group. Questions and Answers:

64 Electronic & Electrical Engineering. Communications Research Group. Thank You All