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Reversible data hiding is a technique that embeds secret information into a host media without loss of host information. Ni et al.'s histogram shifting technique is a high-quality, reversible method for data embedding. However, their technique still suffers from undesirable distortion at low embedding rates and lack of a mechanism to control the stego-image quality, due to all pixels between the peak...
An image classification method based on wavelet transform was brought up, and it adopted the human visual features model and analyzed the image parameter characteristics in smooth and texture regions. It put up optimum carrier image selecting method of original image to be hidden while analyzing the differences between the carrier and being hidden image. On the premise of setting a threshold, it made...
A novel reversible data hiding scheme based on the invariant sum values of pixel pairs is presented in this paper. For each pixel pair, if a certain value is added to one pixel while the same value is subtracted from the other pixel, then the sum of these two pixels will remain unchanged. This value is selected as the half of difference plus 1-bit watermark considering the distortion control and the...
In this paper, a novel halftoning technique for image is designed with genetic algorithm (GA). It is structured on the error diffusion kernel and the resulted halftone image is compared to the one which is originated from the standard error diffusion kernel with the same method by PSNR (peak signal-to-noise ratio).
This paper proposed a superresolution (SR) reconstruction method by combining the cross-diamond-hexagonal search (CDHS) block-matching algorithm (BMA) and the simple block-wise motion vector selection (BWMVS) strategy to obtain stable and high quality reconstruction results. The experimental results showed that the reconstruction quality of CDHS BMA is comparable with full search BMA but the computation...
A low complexity spatial-domain error concealment method is proposed. The edges in lost MB's are detected and recoveried by using neighborhood MB's' gradient data. The lost MB is divided into several smaller subblocks, each pixel in a subblock is directionally interpolated from representative boundary pixels adjacent to the subblock. Experimental results show that the proposed algorithm can recover...
Due to the instability of and possible attacks on the networks, image files transmitted through the networks may encounter losses of data. Such losses may be recovered by retransmitting or by using image processing techniques. The latter has an obvious advantage that the network traffic could be reduced. In this paper, a self-embedding image recovery algorithm based on adaptively rearranged codebooks...
This paper presents a novel image steganographic method that utilizes support vector regression (SVR) to predict the embedded pixel value such that secret data is also embedded into the pixel-value difference between the predicted pixel value and the original pixel value. Due to the significant learning ability in the correlations of training samples by support vector regression, the trained SVR function...
Double-Layered Embedding was proposed by exploiting the least significant bit replacement on gray pixels which are not specified by wet paper codes. DLE adds one to or subtracts one from pixel value when the secret bit to be embedded is not matched the least significant bit of that pixel. However, DLE requires extra space like location map to indicate if the pixel has been changed by adding and subtracting...
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