In this work, we propose new multiresolution techniques for data embedding in imagery. The wavelet extrema of the image are exploited to embed data. We use the wavelet extrema of the dyadic non-orthogonal wavelet transform. These extrema represent high frequency points in the image, hence modifications in their neighborhoods have minor visual distortion. We propose two schemes for data embedding. In the first scheme, the wavelet extrema in the vertical (or horizontal) channel are forced to be at even or odd indices according to the corresponding data bit where one bit is embedded per column (or row) of the image. In the second scheme, data embedding is accomplished by changing the amplitudes of the wavelet extrema relative to the amplitudes of the surrounding wavelet coefficients. The latter scheme is block based rather than column based. Both schemes are robust to common signal processing operations, e.g. JPEG compression, low pass and median filtering, cropping, downsampling followed by upsampling. In addition, The second scheme is robust to geometric distortions and Stirmark attack. The data embedding capacity of the first scheme is in direct proportion to the number of columns in the image, but the capacity of the second scheme is much less. The PSNR of both algorithms is around 44 dB.
['Mohamed F. Mansour', 'Ahmed H. Tewfik']
Techniques for data embedding in image using wavelet extrema