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Asymptotically optimal scalar quantizers for qim watermark detection
 In 2006 International Conference on Multimedia & Expo (ICME
, 2006
"... This paper investigates asymptotically optimal scalar quantizers to address QIM watermark detection with i.i.d. host data and additive noise. Falsealarm probability of detection is chosen as the cost to be minimized, keeping the embedding distortion and the miss probability upperbounded. To avoid ..."
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This paper investigates asymptotically optimal scalar quantizers to address QIM watermark detection with i.i.d. host data and additive noise. Falsealarm probability of detection is chosen as the cost to be minimized, keeping the embedding distortion and the miss probability upperbounded. To avoid the intractability of falsealarm probability, Kullback distance between watermarked and nonwatermarked data is adopted instead. The problem is then to seek the quantizer which maximizes the falsealarm error exponent under distortion constraint. Using Lagrange multiplier minimization, a quantizer updating LloydMaxlike procedure is used to solve the optimization. For experimental aspects, host data and noise have been set gaussian. In comparison with uniform or LloydMax quantizers, it turns out that detection performances can be notably enhanced by using proposed applicationoptimized quantizers. The gain is effective even for small number N of sample at the detector input. However, this gain becomes more substantial as N grows. This also emphasises that good quantizers in terms of distortion are not suitable for detection task. 1.
AN EFFICIENT MARY QIM DATA HIDING ALGORITHM FOR THE APPLICATION TO IMAGE ERROR CONCEALMENT
"... Methods like edge directed interpolation and projection onto convex sets (POCS) that are widely used for image error concealment to produce better image quality are complex in nature and also time consuming. Moreover, those methods are not suitable for real time error concealment where the decoder m ..."
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Methods like edge directed interpolation and projection onto convex sets (POCS) that are widely used for image error concealment to produce better image quality are complex in nature and also time consuming. Moreover, those methods are not suitable for real time error concealment where the decoder may not have sufficient computation power or done in online. In this paper, we propose a datahiding scheme for error concealment of digital image. Edge direction information of a block is extracted in the encoder and is embedded imperceptibly into the host media using quantization index modulation (QIM), thus reduces work load of the decoder. The system performance in term of fidelity and computational load is improved using Mary data modulation based on nearorthogonal QIM. The decoder extracts the embedded features (edge information) and those features are then used for recovery of lost data. Experimental results duly support the effectiveness of the proposed scheme.
Performance Analysis of Scalar DCQIM for OneBit Watermarking
, 2006
"... Quantizationbased schemes, such as scalar DCQIM, have demonstrated performance merits for datahiding problem, which is mainly a transmission problem. However, a number of applications are stated in terms of watermark detection problem (also named onebit watermarking), and this situation has been ..."
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Quantizationbased schemes, such as scalar DCQIM, have demonstrated performance merits for datahiding problem, which is mainly a transmission problem. However, a number of applications are stated in terms of watermark detection problem (also named onebit watermarking), and this situation has been seldom addressed in the literature for quantizationbased techniques. In this context, we carry out a complete performance analysis of uniform quantizersbased schemes with distortion compensation (DC) under additive white gaussian noise. Implementing an exact NeymanPearson test and using large deviation theory, performances are evaluated according to Receiver Operating Characteristic (ROC) and probability of detection error. Optimal DC’s regarding to ROC performances are derived. It is pointed out that falsealarm and miss detection capabilities are jointly optimized by the same DC value. Then, performances are compared with raw quantizedschemes (i.e. without DC) and spreadspectrum (SS) watermarking. It is shown that DCQIM always outperforms QIM and SS for detection task. The gain provided by the DC reaches several orders of magnitude for cases of interest, that is for low watermarktonoise regimes. A short comparison is also provided with respect to the corresponding transmission problem, thus evaluating the loss in performance due to the detection. We conclude in measuring the minimal performance gain that the use of more sophisticated lattice quantizers (than the considered cubic structure) could provide. A local refinement of Liu’s lowerbounds for the optimal DCQIM error exponents is derived.