HighPayload DataHiding Method for AMBTC Decompressed Images Data hiding is the art of embedding data into a cover image without any perceptual distortion of the cover image. Moreover, data hiding is a very crucial research topic in information security because it can be used for various applications. In this study, we proposed a highcapacity datahiding scheme for absolute moment block truncation coding (AMBTC) decompressed images. We statistically analyzed the composition of the secret data string and developed a unique encoding and decoding dictionary search for adjusting pixel values. The dictionary was used in the embedding and extraction stages. The dictionary provides high datahiding capacity because the secret data was compressed using dictionarybased coding. The experimental results of this study reveal that the proposed scheme is better than the existing schemes, with respect to the datahiding capacity and visual quality.

Secret Speech Hiding in Image Based on Quantization Level Modification Data hiding is a form of steganography method that hides secret data in a cover medium like an image, audio or video. In this paper, a method of hiding speech data in a colored image is presented. The main method used in this proposal depends on the technique of quantization level modification with Discrete Wavelet Transform (DWT) to process the cover medium. The latter is used to extract from the RGB of colored images its three bands namely; LowHigh (LH), HighLow (HL), and HighHigh (HH), to be used for embedding the data. As well as Discrete Cosine Transform (DCT) compression is used to compress the speech data by 40% ratio. The embedding method mainly depends upon Absolute Moment Block Truncation Coding (AMBTC) technique for manipulating the binary format of speech. In order to increase the complexity of this proposal, the cover image data is scrambled by using a permutation key that is generated by the Henon map. This proposal also can be utilized to hide any password needed to be extracted by the enduser. The experimental result shows that the average of mean square error (MSE) is 12.16186, peak signal to noise ratio (PSNR) is 33.34402, while the structural similarity (SSIM) is 0.97852.