An Error Resilient Image Camouflaging Scheme for Secret Image Transmission+ Li-Wei Kang
Jin-Jang Leou, Shyi-Shiun Kuo, and Wei-Chih Shen
Institute of Information Science Academia Sinica Taipei 115, Taiwan
[email protected]
Department of Computer Science and Information Engineering National Chung Cheng University Chiayi 621, Taiwan {jjleou, sskuo, wcshen}@cs.ccu.edu.tw
Abstract—In this study, an error resilient image camouflaging scheme for secret image transmission is proposed. In the proposed scheme, at the sender, a secret image is camouflaged into multiple virtual JPEG-2000 images, resulting in multiple cipher-images. Then instead of the secret image, the cipherimages are transmitted to the receiver only. Because both the secret and cipher-images are significant, the cipher-images will not pique the interest of illegal users who may try to get the secret image. At the receiver, if all the cipher-images are completely received, the secret image can be recovered from the cipher-images, whereas if the cipher-images are not completely received, the secret image cannot be recovered. Additionally, because the transmitted JPEG-2000 cipherimages may be corrupted by transmission errors, to enhance the degree of transmission reliability, three proposed techniques, namely, side-match vector quantization, roundrobin like data embedding, and duplicate data embedding, are employed to provide error resilience for robust image transmission.
I.
INTRODUCTION
Image security becomes a very important issue for image transmission over the Internet or wireless network. For secret image transmission, traditional crypto-schemes are not suitable for encrypting a secret image. Several traditional crypto-schemes encrypt a secret image directly into an encoded cipher-image. However, this encoded cipher-image is usually messy and meaningless and easily piques the interest of illegal users who may try to break and recover the encoded cipher-image. That is, the messy and meaningless encoded cipher-image will decrease the security of a cryptoscheme [1]. To solve the above-mentioned problem, Chen, Chang, and Hwang [1] proposed a virtual image crypto-system, in which a secret image is embedded into a virtual image based ______________________________________________________ +This work was supported in part by National Science Council and Ministry of Economic Affairs, Republic of China under Grants NSC 93-2213-E-194-016 and 93-EC-17-A-02-S1-032.
0-7803-8834-8/05/$20.00 ©2005 IEEE.
on vector quantization (VQ). At the sender, the selected virtual image is divided into several blocks. These blocks and some auxiliary parameters are used to create a VQ codebook. Then the VQ codebook is used to encode the secret image to obtain an index set, in which the index for each block in the secret image indicates the corresponding codeword in the codebook. The index set and some employed auxiliary parameters are then encrypted by a data encryption standard (DES)-like crypto-scheme [2] to obtain the final encrypted data for the secret image. Finally, the final encrypted data are embedded into the virtual image by modifying some least significant bits of each pixel in the virtual image. The difference between the virtual image and the cipher-image (i.e., the virtual image with data embedding) is usually limited and imperceptible. At the receiver, after extracting the embedded index set and the auxiliary parameters, the virtual image is used to reconstruct the VQ codebook. The secret image can be recovered by the extracted data and the VQ codebook. As compared with the original secret image, the recovered secret image will have a little quality degradation. To enhance the degree of security, Chang, Tsai, and Chen [3] proposed a visual cryptography scheme for secret color images. At the sender, a secret image is embedded into two virtual color images by using a color index table. At the receiver, the secret image can be recovered by two received virtual color images. The secret image cannot be recovered if only one virtual color image is received. Additionally, Chang and Yu [4] proposed a secret color image sharing scheme based on modified visual cryptography. The scheme can efficiently embed a color image with 256 colors into multiple virtual images. In this study, an error resilient image camouflaging scheme for secret image transmission is proposed. The major contributions of the proposed scheme include: (1) a secret image is camouflaged into multiple virtual JPEG-2000 images [5] and (2) three proposed techniques, namely, sidematch VQ [6], round-robin like data embedding, and
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duplicate data embedding, are employed to provide error resilience for robust image transmission. II.
PROPOSED SCHEME
In the proposed scheme, at the sender, for a secret image, the number of virtual images, NV, should be specified first. Then the secret image will be camouflaged into the NV virtual images, resulting in NV cipher-images. The difference between each virtual image and the corresponding cipherimage is usually limited and imperceptible. Instead of the secret image, the multiple cipher-images will be transmitted to the receiver only. At the receiver, if all the cipher-images are completely received, the secret image can be recovered from the received cipher-images, even the cipher-images are corrupted by transmission errors. A. The Sender At the sender, for an N×N secret image, S, the NV N×N virtual images, V1, V2, …, VNv, will be selected. Each virtual image, Vi, i = 1, 2, …, NV, will be encoded to a JPEG-2000 lossless image with 3 wavelet decomposition levels. Each wavelet subband in the encoded JPEG-2000 lossless image is divided into several nonoverlapping code blocks of a default size of 64×64. As an illustrated example shown in Fig. 1, a 512×512 JPEG-2000 image is divided into 3 wavelet decomposition levels. Level 0 contains the lowest subband, LL0, of size 128×128 of a JPEG-2000 image, which can be treated as a down-sampled version of the original image. Levels 1 and 2 individually contain three subbands denoted by LHi, HLi, and HHi, i = 1, 2, respectively. LH1 contains code blocks 0-3, HL1 contains code blocks 4-7, and HH1 contains code blocks 8-11. LH2 contains code blocks 12-27, HL2 contains code blocks 28-43, and HH2 contains code blocks 44-59. LL0 for each virtual image will be divided into several n×n nonoverlapping blocks. All the n×n blocks from LL0’s of all the NV virtual images are used to form a VQ codebook containing NC codewords (i.e., NC n×n blocks). Here, the codebook size, NC, is equal to the number of the n×n blocks from LL0’s of all the NV virtual images. If the codebook size is set to be smaller than the number of the n×n blocks from LL0’s of all the NV virtual images, some fast VQ codebook training algorithm [7] can be used to create the “reduced” VQ codebook. After the VQ codebook is formed, the secret image, S, is also divided into several n×n nonoverlapping blocks, b0, b1, …, bNb-1. Similar to the camouflaging scheme proposed in [1], the VQ codebook is used to VQ-encode the secret image, S, to find the index, Ii, indicating the closest codeword for each n×n block, bi, i = 0, 1, 2, …, Nb-1, in S. Then the indices for all the n×n blocks in S are embedded repeatedly into each of the NV virtual images, Vi, i = 1, 2, …, NV, to obtain the corresponding cipher-images, Ci, i = 1, 2, …, NV, which will be transmitted to the receiver. Note that the indices for all the blocks in S will be embedded into each of the NV virtual images repeatedly. That is, the set {Ii, i = 0, 1, 2, …, Nb-1}, will be completely
embedded into V1, V2, …, and VNv, respectively. The index data will be duplicated and embedded NV times. The index, Ii, for each n×n block, bi, i = 0, 1, 2, …, Nb-1, in S will be embedded into the corresponding code block in LHi, HLi, or HHi, i = 1, 2, in each selected virtual image, Vi, i = 1, 2, …, NV. Here, a round-robin like data embedding technique is employed. As an illustrated example shown in Fig. 1, the index, Ii, i = 0, 1, …, Nb-1, in S will be embedded into code block j by j = i mod Ncb,
(1)
where Ncb denotes the number of the code blocks in LHi, HLi, and HHi, i = 1, 2, in each selected virtual image. In Fig. 1, Ncb = 60, i.e., code blocks 0, 1, 2, …, 59, I0 is embedded into code block 0, I1 is embedded into code block 1, I2 is embedded into code block 2, …, I59 is embedded into code block 59, I60 is embedded into code block 0, I61 is embedded into code block 1, ..., INb-1 is embedded into code block (Nb 1) mod 60. LL0 4 6 28 32 36 40
5 7 29 33 37 41
0 2 8 10 30 34 38 42
1 3 9 11 31 35 39 43
12 16 20 24 44 48 52 56
13 17 21 25 45 49 53 57
14 18 22 26 46 50 54 58
15 19 23 27 47 51 55 59
Figure 1. An illustrated 3-level wavelet representation of a 512×512 virtual JPEG-2000 lossless image.
The advantages of the employed round-robin like data embedding technique are described as follows. In JPEG2000 [5], the code block is both the basic unit for the entropy coder and the smallest corrupted unit. That is, if transmission errors occur in a code block, the whole data in the corrupted code block will be corrupted simultaneously. For a corrupted code block embedding several index data for S in Vi, i = 1, 2, …, NV, the indices embedded cannot be correctly extracted and the corresponding blocks in S may not be correctly recovered at the receiver. Because the indices for some “isolated” blocks in S are embedded into a code block in Vi, if a code block in Vi is corrupted, the indices that cannot be correctly extracted are belonging to some “isolated” corrupted blocks in S. The isolated corrupted blocks in S with some correctly received neighboring blocks can be well recovered by the employed side-match VQ technique. Hence, the indices for consecutive blocks in S should be embedded into different code blocks in Vi so that consecutive corrupted blocks will not (or seldom) occur in S. Based on the experimental results obtained in this study, using the JPEG-2000 lossless mode, the discrete wavelet transform (DWT) coefficients at the sender (encoder) will be exactly the same as the corresponding decoded DWT coefficients at the receiver (decoder). Hence, the odd-even data embedding scheme for discrete cosine transform (DCT)-based image or JPEG image [8] can be employed to embed one bit into one DWT coefficient at the sender
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(encoder). If the data bit to be embedded is “0,” the DWT coefficient will be forced to be an even number, whereas if the data bit to be embedded is “1,” the DWT coefficient will be forced to be an odd number. That is, if the data bit to be embedded is bj, the DWT coefficient Wi of the odd-even data embedding scheme is determined as Wi + 1 if Wi mod 2 ≠ bj, and Wi > 0, Wi = Wi − 1 if Wi mod 2 ≠ bj, and Wi < 0, W otherwise. i
(2)
Note that each DWT coefficient for data embedding is either unchanged or increased/decreased by 1. The odd-even data embedding scheme is simple and the overall influence to the visual quality of a virtual image is limited and imperceptible. To embed the indices into the corresponding code block, all the indices will be converted to binary bit strings and embedded into the DWT coefficients of the code block (one bit per coefficient) by Eq. (2). Here it is assumed that LL0 of each virtual image is protected by some reliable channel coding technique [9] and will not be corrupted by transmission errors. All the NV virtual images with data embedding form the corresponding NV cipher-images, which will be transmitted to the receiver via one or multiple transmission channels. B. The Receiver At the receiver, after receiving all the cipher-images, LL0 of each cipher-image will be extracted and divided into several n×n nonoverlapping blocks to form the VQ codebook. All the embedded index data will be extracted from the corresponding code blocks if the code blocks are correctly received. Because the index data for the secret image, S, are repeatedly embedded NV times into the NV virtual images, a block index for S can be available if at least one code block embedding the block index in all the NV cipher-images can be correctly received. Each correctly extracted index for S will be used to find the corresponding closest codeword in the VQ codebook so that the corresponding block in S can be recovered. The remaining blocks without correctly extracted indices in S will be recovered by the side-match VQ technique [6]. Using round-robin like data embedding at the sender, the remaining blocks without correctly extracted indices in S are usually isolated and can be well recovered by the employed side-match VQ technique with more neighboring blocks [6]. The proposed scheme can be summarized in Fig. 2. For a color secret image, the proposed scheme can be performed individually to the Y, U, and V components.
Figure 2. The proposed error resilient image camouflaging scheme.
III.
SIMULATION RESULTS
In this study, all the test images (secret and virtual images) are 512×512 color images (N=512). The secret image “Airplane” is shown in Fig. 3, whereas the four virtual images, “Lenna,” “Baboon,” “Sailboat,” and “BlueSky,” are shown in Fig. 4 (NV=4). Each virtual image is encoded as a JPEG-2000 lossless image with 3 wavelet decomposition levels (Ncb=60). LL0 of size 128×128 for each virtual image is divided into 1024 4×4 nonoverlapping blocks (n=4). Hence, the VQ codebook containing 4096 codewords (NC = 4096) and 12 bits are used to indicate a block index. The secret image is divided into 16384 4×4 nonoverlapping blocks (Nb=16384). Note that all the parameters employed in this study can be adaptively adjusted by users. The peak signal to noise ratio (PSNR) is employed in this study as the objective performance measure. The four error-free cipher-images at the sender are shown in Fig. 5, whereas the four corresponding corrupted cipherimages at the receiver are shown in Fig. 6. Note that the error behavior of a JPEG-2000 lossless image is different from that of a JPEG-2000 lossy image. The two recovered secret images from the four error-free cipher-images and from the four corrupted cipher-images are shown in Figs. 7-8, respectively. IV.
CONCLUDING REMARKS
Based on the experimental results obtained in this study, several observations can be described as follows. (1) No matter whether the cipher-images are error-free or corrupted, the secret image can be recovered with acceptable visual quality. (2) If all the NV cipher-images are not completely received, the secret image cannot be recovered. That is because the VQ codebook can be only created based on the lowest subbands (LL0) of the NV cipher-images so that the degree of security can be enhanced. (3) If the number of virtual images is increased, the quality of the recovered secret image will be enhanced due to a larger VQ codebook can be available and index data can be repeatedly embedded more times. However, if the number of virtual images is too large, the transmission bit rate will be greatly increased. (4) The cipher-images using the JPEG-2000 lossless mode are all significant with very high visual quality. Hence, they will not easily pique the interest of illegal users. (5) In the proposed scheme, no traditional crypto-schemes are employed. To enhance the degree of security, similar to [1], the block index data can be encrypted by some DES-like crypto-scheme [2] before being embedded into the cipherimages. As compared with several existing schemes [1], [3]-[4], the proposed scheme has the following good features. (1) The existing schemes [1], [3]-[4] are usually operated on the uncompressed domain, whereas in the proposed scheme, each cipher-image is transmitted using the JPEG-2000 lossless mode (a popular image compression format). (2) Only error-free cipher-images without transmission errors
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are considered in [1], [3]-[4]. However, in the proposed scheme, several error resilient techniques are employed to cope with the corruption problem induced by transmission errors. In this study, an error resilient image camouflaging scheme for secret image transmission is proposed. The proposed scheme can effectively provide secure and robust secret image transmission.
Figure 7. The recovered secret image “Airplane” (PSNR = 33.28dB) from the four error-free cipher-images shown in Fig. 5.
Figure 3. The secret image “Airplane.”
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Figure 8. The recovered secret image “Airplane” (PSNR = 31.06dB) from the four corrupted cipher-images shown in Fig. 6.
(d)
Figure 4. The four selected virtual images: (a) Lenna, (b) Baboon, (c) Sailboat, and (d) BlueSky.
REFERENCES [1]
[2] [3] (a)
(b)
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(d)
Figure 5. The four error-free cipher-images: (a) Lenna (PSNR = 47.38dB), (b) Baboon (PSNR = 47.41dB), (c) Sailboat (PSNR = 47.42dB), and (d) BlueSky (PSNR = 47.18dB).
[4]
[5] [6] (a)
(b)
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(d)
Figure 6. The four corrupted cipher-images: (a) Lenna (PSNR = 16.23dB), (b) Baboon (PSNR = 10.20dB), (c) Sailboat (PSNR = 16.13dB), and (d) BlueSky (PSNR = 22.94dB).
[7]
[8]
[9]
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