The paper introduces a new optimization strategy in LSB steganography that reduces the image degradation rate in the steganographic carrier. We propose an LSB matching steganographic algorithm based on the principles of genetic algorithms, that aims to reuse the binary image color values in a controlled way so that instead of focusing to change the least significant portion of the color representation (LSBs), we remap the secret data in a manner that reduces the color information loss up to a negligible level. The algorithm improves the statistical analysis immunity of the steganographic image and at the same time offers higher PSNR (an average gain of 2,4 dB) than most of the LSB matching algorithms used in our experiments. Because of the flexibility of this approach, our method represents not only a stand-alone steganographic algorithm, but also an extension to other similar algorithms.
The paper introduces a novel approach in steganography based on high dynamic range (HDR) images. Our algorithm employs a two-stage image enhancement/preservation, HDR optimization and smart LSB pixel mapping and data rearrangement [1] in order to produce a robust steganographic image, inconspicuous to both human and computerized analysis. In steganography, reliability represents the degree of resistance to computerized detection algorithms (steganalysis). In order to provide intrinsic resistance to statistical, visual or logical steganalysis, we use a different approach in embedding data as compared to the majority of the steganographic algorithms [3-9]. Using a set of low dynamic-range (LDR) images originating from the main HDR input (with different exposure levels), the secret data can be reliably embedded using smart LSB pixel mapping [1] and select the best set of LDR images that will be chosen to be joined later in the resulting HDR steganographic image. This innovative approach combines the quality obtained using smart LSB pixel mapping and data rearrangement technique [1] with the logical, visual and statistical imperceptibility degree introduced by this algorithm, therefore building a more robust and reliable steganographic model.
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