International Journal of Advancements in Computing Technology Volume 2, Number 2, June, 2010 109 An Improved Algorithm for Data Hiding Using HH-subband Haar Wavelet Coefficients Stuti Bazaj 1 , Sachin Modi 2 , Anand Mohan 3 , S. P. Singh 4 Department of Electronics Engineering Banaras Hindu University, Varanasi-221005, India. 1 stuti.bazaj.ece07@itbhu.ac.in, 2 sachin.modi.ece07@itbhu.ac.in, 3 amohan@bhu.ac.in, 4 spsingh.ece@itbhu.ac.in doi: 10.4156/ijact.vol2.issue2.10 Abstract This paper presents an improved adaptive algorithm for enhanced data hiding under HH-subband Haar Wavelet coefficients of a gray scale host image. The algorithm uses an optimal set of the Wavelet coefficients selected through frequency distribution analysis of the host image to determine the lower and upper bounds of the Haar wavelet coefficients for achieving higher data hiding capacity. Simulation results using JPEG2000 lossless compression on nine standard images indicate that our algorithm provides 17% to 62% increase in hiding capacity with full extraction of hidden data along with stable behavior of impacting stego-image PSNR. Therefore the proposed algorithm can be attractive for enhanced data hiding of radiological images / forensic patterns for secure telemedicine applications. Keywords: Steganography, JPEG2000 Compression, Enhanced Data Hiding, Secure Telemedicine 1. Introduction Inclusion of Discrete Wavelet Transform (DWT) in the JPEG2000 [1] has extended its applications in multimedia data hiding under a host (or cover) image. However, avoiding suspicion by an observer / attacker about hidden data transfer through open channels like Internet frequently requires >35 dB peak signal-to-noise-ratio (PSNR) of the stego-image [2]. This necessitates a compromise between the PSNR [3] and data hiding capacity of an algorithm. Although a number of DWT transforms are available for lossy / lossless image data compression, but recently Haar transform has proved more suitable for multimedia data hiding due to its computational efficiency and hardware implementation simplicity [4, 5]. In general both lossy and lossless compressions can be used but data hiding for specific applications like secure telemedicine and storage / transmission of radiological images or forensic patterns restricts the use of only lossless compressions [6]. This is because retaining the crucial (finer) details of radiological images or forensic patterns becomes prime consideration for their usefulness in diagnosis / prediction by the experts. Further, lossless data compression becomes indispensible for true recovery of hidden data using inverse solution of radiative transfer function which is sensitive to the error or noise in the data. This has motivated selection of lossless data compression under the present study. This paper presents an improved adaptive algorithm for enhanced data hiding under image covers based on adaptive selection of an optimal set of HH-subband Haar wavelet coefficients of the cover image while also offering the best trade-off between the stego-image PSNR and amount of hidden data. The adaptive selection of the optimal HH-subband Haar wavelet coefficient set is achieved based on frequency distribution analysis of the host cover image. Our MATLAB simulation results using JPEG 9.7 [7] lossless compression of Lena, Gibbon, Peppers, Lake, House, Barbara, Cameraman, Hills and Boat stego-images indicate that the developed data hiding algorithm offers 17% to 62% increase in hiding capacity along with stable behavior of impacting stego-image PSNR. Therefore the suggested algorithm can be potentially useful for enhanced data hiding of radiological images / forensic patterns for secure storage / transmission in telemedicine applications.