In this paper, a selective weighting method is used for data embedding to achieve blind watermark detection. In the proposed system, block polarity and activity index modulation are used for the selective weighting. The block polarity is determined based on the number of coefficients that are larger than the median value. The block activity index is the pseudo-quantized block activity that is represented by the sum of absolute differences (SAD) of each coefficient to the median value. The block activity index modulation is performed based on the XOR operation of the randomized watermark and the randomized wavelet blocks polarity. In the block activity index modulation, if any coefficient is located very close to the median, it is vulnerable to attacks because its polarity can easily be changed. In such cases, the coefficient is forced to shift, by the just-noticeable-difference (JND) amount, toward the positive or negative end to enhance the robustness. The watermark embedding is actually performed by the activity index modulation that will modify each coefficient value by a small amount to force the activity to be quantized into a specific region. Simulation results show that the proposed method performs extremely well for Checkmark with non-geometric attacks, such as linear filtering, remodulation, denoising, and compression. The proposed scheme is also robust against image cropping, downsampling, rotation, and columns removal attacks.

The bit-plane clustering technique is applied to high-energy code blocks to enhance the energy compaction by rearranging the column positions in these code blocks. The energy compaction effect can improve the coding efficiency of JPEG2000, which results in an improvement of 6.88% bitrate reduction at 0.1 bpp on average over JPEG2000.

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In this paper, we present a novel energy compaction method, the selective block reordering, which is used with SPIHT (SBR-SPIHT) coding for low rate video coding to enhance the coding efficiency for motion-compensated residuals. The inter-frame coding basically includes three major parts -motion estimation, motion compensation, and motion-compensated residual coding. The motion estimation and overlapped block motion compensation (OBMC) methods of H.263 are used to reduce the temporal redundancy. The motion-compensated residuals are encoded in the wavelet domain. The block-mapping reorganization utilizes the wavelet zerotree relationship that jointly presents the wavelet coefficients from the lowest subband to high frequency subbands at the same spatial location, and allocates each wavelet tree with all descendents to form a wavelet block. The block reordering based on the threshold scan rearranges the significant blocks in the descending order of the energy. Then, the block reordering technique reorders the wavelet sub-blocks recrusively, according to the energy of each sub-block, to yield the maximum energy compaction that allows the SPIHT coding to operate efficiently on the motion-compensated residuals. Simulation results demonstrate that SBR-SPIHT outperforms H.263 by 1.28~0.69 dB on average for various video sequences at very low bit-rates, ranging from 48 to 10 kbps.

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