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TRANSMISSION OF WATERMARKED MEDICAL IMAGE OVER DCT BASED OFDMA WIRELESS SYSTEM

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TRANSMISSION OF WATERMARKED

MEDICAL IMAGE OVER DCT BASED

OFDMA WIRELESS SYSTEM

MD. BELLAL HOSSAIN

Department of Computer Science and Telecommunication Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh.

belal.nstu@gmail.com

Abstract: Watermarking of the radiological patient medical image has become more popular in this new modern era which assist in important decisions from the skilled senior physicians regarding treatment and future care of the issue. High data rate transmission technology requires for the transmission of medical image. Orthogonal Frequency Division Multiple Access (OFDMA) is the emerging system which has recently become a preferred choice in multimedia broadcasting wireless communication systems. In this paper, the issue of the watermarked medical image transmission over discrete cosine transform (DCT)-based OFDMA is investigated over a frequency selective channel for QPSK modulation at different subcarrier mapping schemes. In the watermarking scheme, spatial domain watermarking technique is adapted to embed the patient information as a watermark into lower order bits of the medical image. Experimental results show that watermarked medical image transmission over DCT-based OFDMA system is possible and DCT-DCT-based OFDMA provides better performance than that of the ordinary OFDMA system. The quality of the received medical image is measured with metrices in terms of peak signal to noise ratio (PSNR), mean square error (MSE)and structural similarity index measurement (SSIM). Results also show good exactness in the watermark extraction process.

Keywords: DCT-OFDMA; Electronic Patient Record; Watermarked Medical Image; SSIM

1. Introduction

Now a days, transfer of medical image in a safe and secure way is the needed for the applications of tele-radiology. The production of ownership and prevention of unauthorized manipulation of medical images are becoming an acute issue. Enormous number of medical images are generated everyday as a result managing this medical data is a challenging function faced by radiologist. In hospitals, electronic patient records (EPR) and medical images are gathered in separately which may lead to death of life. To avoid this problem, watermarking technique is introduced where patient data is sealed in the medical image [1]. As a result, confidentiality and security of the medical image almost be maintained. This watermarked medical image is transmitted through high data rate channel. Multicarrier code division multiple access (MC-CDMA) and orthogonal frequency division multiplexing (OFDM) have adopted as new technologies in many wireless communication systems [2]. OFDM reduces the problem of the large bandwidth using the cyclic prefix. Inter-symbol Interference (ISI) is the challenging problems for the transmission of high data rate channel. ISI degrades the system performance which is caused by multi-path fading. OFDMA system has the ability to overcome the ISI by the frequency domain equalizers. OFDM assigns one block (in time) to one user, OFDMA assigns different groups of subcarriers (in frequency) to different users. Each user in an OFDMA system is usually given certain subcarriers during a certain time to communication [3, 4].

Due to the growth of technological advance, wireless transmission of the medical images and medical video can be easily performed over multipath channels. Image transmission over multicarrier code division multiple access (MC-CDMA), orthogonal frequency division multiplexing (OFDM) and GSM systems have attracted in much consideration in the literature. The issue of the image transmission over MC-CDMA system was studied. Image transmission over a space-time coded OFDM system was proposed in [5-7]. In this issue, to the best of the authors’ knowledge, watermarked medical image transmission over DCT-based OFDMA system has not been enough announced and investigated.

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The remainder of this paper is composed in the following way. Section 2 explains the medical image watermarking schemes. Section 3derives the system model of the DCT based OFDMA system. Subcarriers mapping schemes are discussed in section 4. Section 5 explains the image quality metrices. Section 6 introduces the simulation scenario and experimental results. Finally, section 7 concludes the paper.

2. Medical Image Watermarking

The doctor can embed the patient’s diagnostic data into the cover image and enjoin for second opinion to some specialist doctor located in some remote area. The second specialist doctor can embed his own diagnosis data and send back to the first doctor [1]. So, watermarking in medical images is frequently used for content authentication, storage, security and saving bandwidth effectively. This work discusses how to watermark in the medical image, transmit through DCT based OFDMA systems and how to recover the medical image. EPR hiding watermarks attempt at reducing the storage space as well as to avoid detachment of the medical cover image and patient’s data. When the patient’s data such as patient’s demographic data, patient name, ID, sex, age, remote physician’s opinion etc. and medical cover image were gathered separately excessive memory is required as well as when transmitting through latest communication system it brings transmission overheads [8]. In order to efficiently use the memory and network bandwidth, patient’s data can be embedded as EPR into the medical cover image. In this approach, the text data of the patient information is embedded into the lower order bits (LSBs) of the medical image pixels as a watermark using spatial domain technique [9].

3. DCT Based OFDMA System Model

The text data of the patient information is embedded into the medical image. This watermarked medical image is used to transmit the image over the DCT based OFDMA system by converting it to a binary form suitable to be inserted and processed by the DCT based OFDMA system.

Fig. 1. System model of medical image transmission over DCT based OFDMA system

The OFDMA transmitter starts with an encoder then a modulation of the input signal using Quadrature Phase Shift Keying (QPSK). Let xn represent the modulated source symbols. A block of N modulated symbols for each user is mapped to corresponding subcarriers producing a block of M symbols. Then the inverse discrete cosine transform is performed. After that a cyclic prefix (CP) is added to the resulting signal. Finally, the resulting signal is transmitted through the wireless channel. After the IDCT, the signal can be expressed as follows [10-12]:

̅ 2 2 1

2

where is signal after subcarrier mappings, and M is the length of the IDCT (M = Q.N). Q is the bandwidth expansion factor of the symbol sequence. If all terminals transmit N symbols per block, the system can handle Q

simultaneous transmissions without co-channel interference. βn is given by,

√ , 0

1 , 1, 2, … , 1

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At the receiver, the CP is removed and the received signal can be expressed as follows:

,

where ̅ is an M×l vector representing the transmitted samples, r is an M×l containing the received

samples. The matrix H is an M×M circulant matrix describing the multipath channel. Equalization is performed in frequency domain using minimum mean square error. Therefore, the received signal is transformed to frequency domain using M-point DFT. Then after applying MMSE equalization, M-point IDFT is performed. After that, M-point DCT in order to perform subcarrier de-mapping. Finally, the demodulation and the decoding processes are performed [10].

4. Subcarrier Mapping Methods

There are two methods of assigning the M frequency domain modulation symbols to subcarriers: distributed subcarrier mapping and localized subcarrier mapping. In the localized subcarrier mapping scheme, each user’s data is transmitted with consecutive subcarriers, while in the distributed subcarrier mapping, each user’s data is transmitted with distributed subcarriers. The distributed subcarrier mapping scheme with equidistance between occupied subcarriers throughout the whole-band is called the interleaved scheme. The interleaved scheme is more robust against frequency selective fading because symbols are spread across the whole band [13]. An example system with 3 users, 12 subcarriers and 4 subcarriers allocated per user is illustrated in Fig. 2. In this paper, LOFDMA denotes the localized OFDMA system and the IOFDMA denotes the interleaved OFDMA system.

Fig. 2. Subcarrier allocation methods for multiple users (3 users, 12 subcarriers, and 4 subcarriers allocated per user) [13]

5. Medical Image Quality Metrices

In this paper, the PSNR, the MSE and the SSIM metrices are applied to evaluate the quality of the received image. A lower PSNR, SSIM and higher MSE indicate that the quality of the reconstruction image is low. Therefore, a higher PSNR, SSIM and a lower MSE is required. The PSNR can be expressed as follows [14]: PSNR (dB) = 10log

where is the maximum pixel value in the medical image. The MSE is defined as follows:

MSE = ∑ ∑ , ,

where is number of pixels, It and Ir are the transmitted and received medical images.

PSNR or MSE may not correlate well with the human perception of quality. SSIM is better than PSNR because SSIM involves one number per pixel, while PSNR gives an average value for the whole image. SSIM is designed to improve on traditional methods such as peak signal-to-noise ratio (PSNR) and mean squared error (MSE). The structural similarity measurement system divides the measurement into three mutually independent components: luminance, contrast and structure [14].

The three components are combined to obtain the overall similarity measure given by SSIM (x, y).

, , , , , ,

6. Simulation Scenario and Results

At first stage, we will make a watermarked medical image by patient data as a watermark is inserted into the MRI human head image. Patient data may be name, age, sex, symptom, blood pressure and patient primary diagnostic information. In this thesis, the hints of patient data are the following:

Name: Md. Bellal Hossain, Age: 35 years, Blood Pressure: 120/80, Symptom: Migraine Headache, Hospital: Lab Aid (Dhanmondi Branch).

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In the second stage, watermarked medical image is transmitted through the DFT-OFDMA and DCT-OFDMA system over frequency selective Stanford University Interim (SUI-3) channel. In the third step, the decoding system of DFT-OFDMA and DCT-OFDMA is to reconstruct the watermarked medical image. Finally, the patient data and cover medical image is to extract from the watermarked medical image. From the original cover medical image and reconstructed medical image, we will measure MSE, PSNR and SSIM which select the quality of reconstructed medical image. We will compare with different types of subcarriers mapping at various channel SNR.

To evaluate the performance and efficiency of DFT-OFDMA and DCT-OFDMA systems, MRI Human head image (256 × 256×3) is used as an input to the simulation framework. The simulation parameters are as shown in Table 1.

Table 1: Simulation parameters

Simulation Parameter Value

FFT Size 512 symbols

Input block size 128 symbols

Cyclic prefix size 20 samples

Medical image size 256×256×3

Channel coding Convolutional code with rate ½

Modulation type QPSK

Subcarriers mapping Interleaved and localized

Channel model SUI3 channel

Noise environment AWGN

Equalizer type MMSE equalizer

The issue of watermarked medical image transmission over DCT based OFDMA systems for different subcarriers mapping schemes is investigated. In the simulated OFDMA system, each user occupies 128 subcarriers. The total number of subcarriers M = 512 and the number of user’s L = 4. In each simulation, all subcarriers are assigned among all users according to the subcarriers mapping method used. QPSK modulation schemes are used to generate a transmitted block for each user. MMSE equalization is assumed. The channel models used for simulations is the SUI-3 channel model. A convolutional code with memory length 7 and octal generator polynomials (133,171) is chosen as the channel code. The transmitted MRI human head image for all users of size 256 x 256 × 3 is shown in Fig. 3.

Fig. 3. The Transmitted MRI Human Head Image

6.1. MSE performance

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Table 2: MSE values of the received medical image over the DCT-OFDMA and DFT-OFDMA

SNR (dB) DCT-OFDMA DFT-OFDMA

Interleaved Localized Interleaved Localized 0 0.0067 0.0055 0.1909 0.1918 5 0.0036 0.0018 0.1739 0.1715

10 1.81e-05 0 0.1470 0.1498

15 0 0 0.1003 0.0905

20 0 0 0.0575 0.0639

25 0 0 0.0183 0.0152

30 0 0 0.0021 0.0014

35 0 0 0.0017 0.0016

40 0 0 1.55e-06 5.09e-06

Fig. 4. MSE against SNR of the Received Medical Image over the DCT-OFDMA and DFT-OFDMA

6.2. PSNR performance

In this subsection, the PSNR performance of the received medical image over the DCT-OFDMA and DFT-OFDMA systems for QPSK is studied. The PSNR values are systematized in Table 3. Fig.5 shows the variations of the PSNR of the received medical image with SNR when transmitting the medical image through DCT-OFDMA and DFT-DCT-OFDMA systems at QPSK modulation at different subcarriers mapping schemes. As illustrated in Fig. 5, it is observed that PSNR is increased as channel SNR is increased. It is clear that the DCT-OFDMA system provides significantly better PSNR performance than that of the DFT-DCT-OFDMA system for QPSK and the difference more than 25dB, due to the energy compaction property of the DCT based SC-FDMA system, which makes most of the samples transmitted close to zero leading to a reduction in the effect of ISI. Results also show that the interleaved system gives the nearly same PSNR values of localized system.

Table 3: PSNR values of the received medical image over the DCT-OFDMA and DFT-OFDMA

SNR (dB) DCT-OFDMA DFT-OFDMA

Interleaved Localized Interleaved Localized

0 14.00 14.15 7.19 7.17

5 17.19 18.59 7.59 7.66

10 22.64 ∞ 8.32 8.25

15 ∞ ∞ 9.90 10.43

20 ∞ ∞ 12.42 12.00

25 ∞ ∞ 17.53 18.64

30 ∞ ∞ 30.20 30.85

35 ∞ ∞ 28.06 31.31

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Fig. 5. PSNR against SNR of the Received Medical Image over the DCT-OFDMA and DFT-OFDMA

6.3. SSIM performance

The goal of this subsection is to analyze SSIM performance of the received medical image over the DCT-OFDMA and DFT-DCT-OFDMA systems for QPSK. The SSIM values are presented in Table 4. Fig.6 shows the variations of the SSIM values of the received medical image with channel SNR when transmitting the medical image through DCT-OFDMA and DFT-OFDMA systems at QPSK modulation at different subcarriers mapping schemes. As illustrated in Fig. 6, it is mentioned that SSIM values is increased as channel SNR is increased. It is clear that the DCT-OFDMA system gives best SSIM values than the DFT-OFDMA system for QPSK and the difference more than 25dB. The SSIM performance in DCT-LOFDMA and DCT-IOFDMA are nearly the same. SSIM is better than PSNR because SSIM involves one number per pixel, while PSNR gives an average value for the whole image. It is seen from the Table 3 and 4 that the SSIM and PSNR value of DCT-IOFDMA is 0.6036, 14 respectively at channel SNR = 0dB. But, we see from the Fig. 7 that the clarity of the received image is not full of high quality, having its some noisy but fairly clear to see. From the above discussion, it appears that SSIM gives the accurate value than that of PSNR.

Table 4: SSIM values of the received medical image over the DCT-OFDMA and DFT-OFDMA

SNR (dB) DCT-OFDMA DFT-OFDMA

Interleaved Localized Interleaved Localized 0 0.6036 0.5866 0.0136 0.0138 5 0.9073 0.9138 0.0215 0.0216

10 0.9979 1 0.0329 0.0306

15 1 1 0.0633 0.0728

20 1 1 0.1483 0.1388

25 1 1 0.5117 0.5872

30 1 1 0.8962 0.9049

35 1 1 0.9074 0.9182

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Fig. 6. SSIM against SNR of the Received Medical Image over the DCT-OFDMA and DFT-OFDMA

6.4. Analysis of perception quality of medical Image

Figs. (7-9) show the simulation results when transmitting the medical image through the DCT-OFDMA and DFT-OFDMA systems at different SNR values. To analyze the perceptibility of the received watermarked medical images over DCT-OFDMA and DFT-OFDMA systems, the received medical images at SNR= 0dB are selected and shown in Fig. 7 for QPSK. It is clear that the quality of the received images using the DCT-OFDMA system is better than that of the DFT-DCT-OFDMA system. The transparency of the received images obtained through DCT-OFDMA is very high quality.

To analyze the perceptibility of the received watermarked medical images over DCT-OFDMA and DFT-OFDMA systems, the received medical images at a SNR= 20dB are selected and shown in Fig. 8 for QPSK. It is clear that the quality of the received images using the DCT-LOFDMA systems is same as the DCT-IOFDMA system which is infinity PSNR and the highest value of SSIM. The picture quality of the received images through DFT-OFDMA is very poor. To analyze the perceptibility of the received watermarked medical images over DCT-OFDMA and DFT-OFDMA systems, the received medical images at a SNR= 40dB are selected and shown in Fig. 9 for QPSK. It is clear that the quality of the received images using the DCT-OFDMA systems is same as the DFT-OFDMA system which is infinity PSNR and the highest value of SSIM. The picture quality of the received images through DCT-OFDMA and DFT-OFDMA is very high quality. However, both systems are able to reconstruct watermarked medical images over a frequency selective channel when the channel SNR at 40dB.

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Fig.8. Simulation results for SNR=20dB. (a) DCT-IOFDMA, PSNR=∞dB, SSIM=1 (b) DCT-LOFDMA, PSNR=∞dB, SSIM=1 (c) DFT-IOFDMA, PSNR=12.42dB, SSIM=0.1483 (d) DFT-LOFDMA, PSNR=12dB, SSIM= 0.1388

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7. Conclusion

In this paper, the performance of watermarked medical image transmission over DCT based OFDMA has been evaluated and compared to the performance of traditional DFT based OFDMA for QPSK modulation at different subcarriers mapping schemes. The mathematical model for the DCT based OFDMA system has been derived. The simulation results have been shown that the DCT based OFDMA system provides better performance than that of the DFT base OFDMA system, based on the different types of image quality metrices such as MSE, PSNR and SSIM because the DCT has excellent spectral energy compaction property. DCT uses only real arithmetic’s rather than complex arithmetic’s used in the DFT which reduces the signal processing complexity. From the simulation results, it is also observed that DCT based OFDMA systems are able to efficiently transmit medical image over frequency selective channel faithfully above 10dB, but DFT based OFDMA systems are able above 40dB.

REFERENCES

[1] U. R. Acharya, D. Anand, P. S. Bhat, and U. C. Niranjan, “Compact storage of medical images with patient information,” IEEE Transaction on Information Technology in Biomedicine, vol. 5, no. 4, pp. 320-323, Dec. 2001.

[2] K. Fazel and S. Kaiser, “Multi-Carrier and Spread Spectrum Systems,” John Wiley & Sons Ltd., 2003. [3] S. C. Yang, “OFDMA System Analysis and Design,” Artech House, 2010

[4] R. Nogueroles, M. Bossert, A. Donder and V. Zyablov, “Improved performance of a random OFDMA mobile communication system,” in Proc. Of the IEEE VTC, vol. 3, pp. 2502-2506, May 1998.

[5] E. M. El-Bakary, E. S. Hassan, O. Zahran, S. A. El-Dolil, and F. E. Abd El-Samie, “Efficient image transmission with multi-carrier CDMA,” Wireless Personal Communications, vol. 69, no. 2, pp. 979-994, Mar. 2013.

[6] Y. Sun and Z. Xiong, “Progressive image transmission over space-time coded OFDM-based MIMO systems with adaptive modulation,” IEEE Trans. on Mobile Computing, vol. 5, no. 8, pp. 1016-1028, 2006.

[7] J. Perez-Sevilla and D. C. McLernon, “Medical image transmission over GSM cellular systems,” Electronics Letter, vol. 36, no. 16, pp. 1367-1368, Aug. 2000.

[8] D. Anand., and U. C. Niranjan, “Watermarking medical images with patient information,” Proceedings of the International Conference of IEEE Engineering in Medicine and Biology, pp. 703-706, 1998,

[9] M. S. Sutaone and M. V. Khandare, “Image based steganography using LSB insertion technique,” IET International Conference on Wireless Mobile and Multimedia Networks, 2008.

[10] P. Tan and N. C. Beaulieu, “A comparison of DCT-based OFDM and DFT-based OFDM in frequency offset and fading channels,” IEEE Transaction on Communication, vol. 54, no. 11, pp. 2113–2125, Nov. 2006.

[11] A. V. Oppenheim, R. W. Schafer, and J. R. Buck, “Discrete-Time Signal Processing,” 2nd ed., Prentice Hall, NJ, 1999.

[12] N. Ahmed, T. Natarajan, and K. Rao, “Discrete cosine transform,” IEEE Transactions on Computers, vol. 23, no. 1, pp. 90–93,1974. [13] H. G. Myung, J. Lim, and D. J. Goodman, “Single Carrier FDMA for Uplink Wireless Transmission,” IEEE Vehicular Technology

Magazine, vol. 1, no. 3, pp. 30-38, Sep. 2006.

Figure

Fig. 1. System model of medical image transmission over DCT based OFDMA system
Fig. 2. Subcarrier allocation methods for multiple users (3 users, 12 subcarriers, and 4 subcarriers allocated per user) [13]
Table 1: Simulation parameters
Table 2: MSE values of the received medical image over the DCT-OFDMA and DFT-OFDMA
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References

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