a high performance multi-layer reversible data hiding scheme using two-step embedding authors:...

A High Performance Multi-layer Reversible Data Hiding Scheme Using

Two-Step Embedding

Authors: Jinxiang Wang Jiangqun Ni Jinwei Pan

Outline

Histogram Shifting on Pixel Differences HS for single layer embedding HS for multi-layer embedding

Two-Step Embedding Framework (TSE) Improvement for Reduction the Location Map Traditional location map generation The improvement scheme for reduction location map size

Embedding Process Extraction Process Experimental Results

Histogram shifting algorithm

Traditional histogram shifting algorithm (HS) Traditional histogram shifting algorithm is based on the pixel values,

which utilizes the redundancy of the host image statistical information to

hide secret data, the sketch map is shown as follows.

Grayscale value

Fre

quen

cy

Peak point

Lowest point

non-zero point situation

Zero point Grayscale value

Grayscale value

Fre

quen

cy

Grayscale value

Fre

quen

cy

Peak point

zero point situationF

requ

ency

Zero point

Peak point

wEmbedding

Note:1) The extraction is performed in the reverse

order as the embedding process. 2) The side information (peak/zero points) should

be additionally transmitted to the receiver for reversible recovery.——No blind

3) The histogram shifting is extended to the pixel differences or predictive errors to improve the performance

Histogram shifting on the pixel differences

1| |i i id x x

d

FrequencyHistogram shifting

d’

Pixel differences calculation ‘d’

Generate the histogram of pixel differences

Generate the marked pixel differences ‘d’’

1 1

1 1

,

,i i i i

ii i i i

x d x xy

x d x x

Generate the marked pixel values ‘y’

'

1, ,

,

,

i i

i i i

i

d d U P Z

d d w d P

d otherwise

Note:1) P and Z should be additional

transmitted to the receiver.2) The process represents the

single layer embedding

Multi-layer embedding When the size of secret data is large, the generated stego-image (stego-differences) is repeatedly considered as a new cover image (cover differences) to perform a new round histogram shifting to

hide more message. The multi-layer embedding is described as follows.

Stego- image

Pixel differences

Original

image

1th layer …… mth layerMarked pixel differences

P1,Z1 Pm,Zm

Note: the side information {Pi,Zi | 1≤i ≤m} should be additional transmitted

Two-Step Embedding Framework

Purpose: 1) To solve the issue of needing to transmit the side information

additionally. —— No blind

2) To ensure the optimal peak/zero points selection among HS to

improve the performance. TSE for single layer embedding

A1

optimal selectionhistogram peak / zero points

first

LSB replacement

Replaced LSBs

Stego Image

pixel differences

Originalimage

second

StegoA2

Stego

TSE for multi-layer embeddingNote: 1) TSE is employed in the final layer embedding;2) The LSB substitution is performed on the stego-pixels.

mth layer (TSE)

A1

A2

Stego- image

Pixel differences

Original

image

1th layer …… (m-1)th layer

Framework of two-step embedding for multi-layer embedding

The characteristic of TSE:1) TSE is an improved LSB based scheme, which hides the side

information in the LSBs of the chosen stego-pixels in A1 to achieve the blind requirement.

2) Without consuming some intact fixed area to hide side information in the traditional schemes, our scheme utilizes the LSB in the stego-pixels.

3) The flexible optimal peak/zero point ensures the better performance.

Improvement for Reduction the size of Location Map

Location map: Due to the modification on the pixel differences to hide

secret data, the marked differences may be not in the normal range [0, 255] for a 8-bit grayscale image.

Thus the location map is needed to record the special overflow/underflowed pixels and embedded in the cover image together with the secret message.

The location map can be recovered by the receiver to lossless restore the original image.

Traditional method for the location map generation

1 1( ') ( ) 'i i i i i i i iy x x d x d d d m

Each layer HS embedding leads to at most 1 unit distortion between marked difference di’ and original difference di. Thus, the difference between the stego-pixel and original pixel via m - layer embedding is

The potentially overflowed/underflowed pixels (POPs) is in the range and should be specially handled as follows.

0, 1 255 1,255m m

:POPs

Cover image

1) Locate all the POPs in the interval 0, 1 255 1,255m m

2) Use histogram narrowing technique (HN) to narrow the POPs to the middle grayscale value and generate a new narrowed cover image I’

'

( ) [0, 1]

( ) [255 1,255]i

i i

i

x m I i m

x x m I i m

x otherwise

3) After m-layer embedding on the narrowed image I’, no overflow/underfow occurs. 4) Generate a same sized location map with ‘1’ and ‘0’ to indicate the narrowed pixels and non-narrowed pixels. 5) Compress the location map and hide the compressed version in the cover image.

General idea: we exchange the histogram narrowing technique int

o the final layer embedding process and only indicate the actually overflowed/underflowed pixels (AOPs), which is a subset of the POPs.

Thus the improved location map with less ‘1’ in it will be easier to be compressed. The detailed TSE for the reduction of the location map is described as follows.

Improvement for Reduction the size of Location Map

R_POPs in A2

w={w(1), w(2), w(3)}

w(1)

w(2)

LM + SI

POPs

R_POPs in A1

A1

HS embedding

LSB replacement

HS embedding

LM

LSBs

AOPs

:POPs

A1

A2

Cover image Pixel differences

HS embeddingA1

A2

w(3)+LSBs

The sketch map of TSE for location map reduction

Embedding Process

1) Calculate the pixel differences

2) Determine the embedding layer ‘m’

3) Identify the POPs in cover image with gray value in the range

4) Perform the front (m-1)-layer embedding

5) Implement the TSE in the final layer embedding.

0, 1 255 1,255m m

Note: Among the process, the compressed location map and side information for each layer are together hidden in the image in step 5. Moreover, the histogram narrowing technique is utilized in the same step.

Extraction Process

1) Divide the stego-image into A1 and A2 as did in embedding side, and collect the side information from the LSBs of the marked pixels in A1.

2) Decompress and generate the location map to indicate the actually overflowed/underflowed pixels (AOPs). Perform the inverse HN operation on the AOPs.

3) Perform the m-layer extraction operation in the inverse order and recover the original cover image.

The TSE framework extended to other prediction errors

One prediction model:

X O X O X

O X O X O

X O X O X

O X O X O

X O X O X

(1)(2) (4)

(3)

xx x x

x

(a) (b)

1 2 3 4

4

x x x xx

%

~

( )d x x

The multilayer embedding is iteratively performed between the ‘cross’ set and ‘round’ set . And the successive prediction utilizes the generated stego-pixels in opposite set. The (i+1) th layer embedding process is illustrated.

' 1 ' 1O O OO (1) (2) (3) (4) 4 O O ( ) O O ( ) Oi i i i i i i i i i i i i iX X X X X d d d

% % %（）

Experimental Results

The Efficiency for Location Map Reduction between the traditional method and our improved scheme

| |_ 100%t i

i

LM LME Map

LM

Where LMt and LMi denote the size of traditional and improved location map, respectively.

mCover image(512×512)

chosen schemes1 2 3 4 5

Lena

Traditional location map [18] 20 20 20 20 20

Improved location map 20 20 20 20 20

Overflow/Underflow N N N N N

E_Map -- -- -- -- --

Peppers



Overflow/Underflow Y Y Y Y Y

E_Map 0% 9.1% 19.4% 63.6% 108.6%

Baboon




E_Map 600% 633.3% 785.7% 755.6% 935.3%

F16




E_Map -- -- -- -- --

Goldhill




E_Map -- -- -- -- --

Boat




E_Map 11.1% 50% 73.9% 112.9% 282.1%

Comparison Between the TSE in Pixel Differences, in Predictive Errors and Other Schemes

TSE_PD_TM: TSE + Pixel differences + traditional location map TSE_PD_IM: TSE + Pixel differences + improved location map TSE_PE_IM: TSE + prediction errors + improved location map

[18] Tai W. L., Yeh C. M., Chang C. C.: Reversible Data Hiding Based on Histogram Modification of Pixel Differences. IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 6, pp. 906-910 (2009)[19] Luo L., Chen Z., Chen M., Zeng X., Xiong Z.: Reversible Image Watermarking Using Interpolation Technique. IEEE Trans. Inf. Forensics Security, vol. 5, no. 1, pp.187–193 (2010)[13] Hwang J., Kim J., Choi J.: A Reversible Watermarking Based on Histogram Shifting. In: Proc. International Workshop on Digital Watermarking. pp. 348-361. Jeju Island, Korea (2006)

Conclusion

1) The proposed scheme exploits TSE to solve the problem of communicating side information. The TSE framework also ensures the adoption of optimal peak and zero point pair in each layer for high performance reversible data hiding.

2) An improved location map, which indicates only the actual overflow/underflow pixels, is constructed to facilitate the compression of location map and further increase the embedding capacity.

Thank you!

a high performance multi-layer reversible data hiding scheme using two-step embedding authors:...

Documents

multilayer embedding

histogram of pixel differences

embedding process

pixel differences hs

single layer

histogram shifting

pixel differences p1

final layer