An Audio Steganography Based on Run Length Encoding and Integer Wavelet Transform

Secured Reversible matrix embedding based on dual image using Integer wavelet and Arnold Transform

According to the correlated characteristic of remotely sensed multispectral images (RSMI) in the spectral and spatial domains, an effective and lossy YCrCb+IWT compression algorithm is proposed. The algorithm combines YCrCb transform with integer wavelet transform (IWT) to compress data, and data redundance of spectral and spatial domains is removed respectively. The important degree of the each subband is determined according to the energy of the each subband. Furthermore, each subband is quantified using adaptive threshold according to their important degree, then fixed bit-plane coding and Run Length Encoding are individually used to the quantified data of every subband and important graph. When implementing compression algorithm, in order to ensure better quality of reconstructed image, the compression with little distortion is utilized for luminance information Y. Simultaneously, in order to obtain higher compression ratio, the compression with biggish distortion is carried out for chrominance information Cr and Cb. The simulation experiment indicates that this algorithm can receive good compression performance of average CR≥ 7 and average PSNR ≥ 33dB for RSMI of different content and texture. In addition, the algorithm requires small storage and is easy to be realized in hardware, so it is suitable for space-borne application.

Modern day information age is enriched with the advanced network communication expertise but unfortunately at the same time encounters infinite security issues when dealing with secret and/or private information. The storage and transmission of the secret information become highly essential and have led to a deluge of research in this field. In this paper, an optimistic effort has been taken to combine graceful graph along with integer wavelet transform (IWT) to implement random image steganography for secure communication. The implementation part begins with the conversion of cover image into wavelet coefficients through IWT and is followed by embedding secret image in the randomly selected coefficients through graph theory. Finally stegoimage is obtained by applying inverse IWT. This method provides a maximum of 44 dB peak signal to noise ratio (PSNR) for 266646 bits. Thus, the proposed method gives high imperceptibility through high PSNR value and high embedding capacity in the cover image due to adaptive embedding scheme and high robustness against blind attack through graph theoretic random selection of coefficients.

This paper proposes an information hiding method that ex-ploits the Integer Wavelet Transform (IWT) and Replace Function. First, the cover image is transformed into frequency coefficients through the IWT. Then, Run-Length Encoding (RLE) technique is used to compress the secret message. Furthermore, the compression result is embedded into the frequency coefficients by using the Modulus Function and Least Significant Bit (LSB) Matching. When the receiver receives the stego image, the compression result can be obtained from the frequency coefficients of the stego image by using the Modulus Function and Binary Function. In the experimental result, embedding capacity of the secret message and the quality of the stego image are good.

The integer wavelet transform (IWT) is dealt with. For for image compression performance, it is known that the IWT has a worse performance than the discrete wavelet transform (DWT). We analyse the IWT signal representation mechanism with respect to the DWT one, in order to explain this difference. Insight into this mechanism suggests a simple, computationally efficient yet very effective way to improve the IWT compression performance up to the DWT level. Simulation results are presented for both natural and synthetic images, these latter being more critical for the IWT; it is shown that the proposed method permits one to fill the gap between the IWT and the DWT performance.

The rapid development on the field of communication require a secure exchange of information between the sender and the reciepient. Information hiding techniques are widely used in the field of communication such as military applications, scientific research etc. Information hiding is a general process or term which deals with embedding the message for communication in the content. Otherwise we can say that it refers to either producing the data to be hidden making the existence of secret information to be unnoticeable. This process leads to prevent unauthorized access. There are two inputs in the steganography process, one is the cover object and the other is secret object, both these inputs may be image, video, audio e.t.c. Depending upon these cover objects, it can be categorized into image steganography, video steganography, audio steganography e.t.c. In this paper both cover and secret objects are image. In this paper image steganography is performed with IWT (Integer Wavelet Transform). Normally the steganography process is performed with DWT (Discrete Wavelet Transform), while applying this transform there exists floating point coefficients,which leads to floating point truncation results in loss of information, to avoid this problem we choose IWT. Arnold transform is an image scrambling technique applied to the secret image to ensure security to it.

In the present era of the internet, image watermarking schemes are used to provide content authentication, security and reliability of various multimedia contents. In this paper image watermarking scheme which utilizes the properties of Integer Wavelet Transform (IWT), Schur decomposition and Singular value decomposition (SVD) based is proposed. In the suggested method, the cover image is subjected to a 3-level Integer wavelet transform (IWT), and the HH3 subband is subjected to Schur decomposition. In order to retrieve its singular values, the upper triangular matrix from the HH3 subband’s Schur decomposition is then subjected to SVD. The watermark image is first encrypted using a chaotic map, followed by the application of a 3-level IWT to the encrypted watermark and the usage of singular values of the LL-subband to embed by manipulating the singular values of the processed cover image. The proposed scheme is tested under various attacks like filtering (median, average, Gaussian) checkmark (histogram equalization, rotation, horizontal and vertical flipping) and noise (Gaussian, Salt & Pepper Noise). The suggested scheme provides strong robustness against numerous attacks and chaotic encryption provides security to watermark.

With the era of rapid technology in multimedia, the copyright protection is very important to preserve an ownership of multimedia data. This paper proposes an image watermarking scheme based on Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). The binary watermark is scrambled by Arnold transform before embedding watermark. Embedding locations are determined by using variance pixels. Selected blocks with the lowest variance pixels are transformed by IWT, thus the LL sub-band of 8×8 IWT is computed by using SVD. The orthogonal U matrix component of U3,1 and U4,1 are modified using certain rules by considering the watermark bits and an optimal threshold. This research reveals an optimal threshold value based on the trade-off between robustness and imperceptibility of watermarked image. In order to measure the watermarking performance, the proposed scheme is tested under various attacks. The experimental results indicate that our scheme achieves higher robustness than other scheme under different types of attack.

Health IoT deals with sensitive medical information of patients, therefore security concerns need to be addressed. Confidentiality of Electronic Health Record (EHR) and privacy are two important security requirements for IoT based healthcare systems. Recently, watermarking algorithms as an efficient response to these requirements is in the spotlight. Further, as smart city-based applications have to react to real-time situations, efficient computation is a demand for them. In this paper, a secure, lightweight, reversible, and high capacity watermarking algorithm with tamper detection capability is proposed for IoT based healthcare systems. The scheme has applied Integer Wavelet Transform (IWT) and chaotic map for efficiency and increasing security. EHR is encrypted and then embedded into the Least Significant Bits (LSB) of wavelet coefficients of medical images. The proposed method has been extensively tested for various color and grayscale commonly used medical and general images. Investigations on experimental results and criterions such as Peak Signal to Noise Ratio (PSNR) and Bit Error Ratio (BER) above 45.41 dB and 0.04, respectively, for payload of 432,538 bits indicate that the proposed method, besides providing security, being reversible, tamper detection capability, and high embedding capacity, has high imperceptibility and adequate resistance against different types of attacks.

Steganography is a technique for embedding digital information inside another digital medium such as text, images, audio signals or video signals, without revealing its presence in the medium. In video steganography, a video file will be used as a cover medium within which any secret message can be embedded. In steganography, the secret information can be hidden either directly by altering the pixel values of the images in the spatial domain or in the frequency components of the images after transforming the images into frequency domain by using transformation algorithms such as DCT (Discrete Cosine Transform), DWT(Discrete Wavelet Transform) and IW(Integer Wavelet Transform). In this paper, secret data are embedded inside a video file using both the methods, spatial and frequency, and the outcomes are analysed and compared. Results are compared based on PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), BER (Bit Error Rate) and Standard Deviation. The findings of this study are given as suggestions for further enhancement.

The Integer Wavelet Transform (IWT) has proved particularly successful in the area of embedded lossy-to-lossless image coding. One of the possible methods to realize the IWT is the lifting scheme. Here we construct a new class of IWTs parameterized simply by one free parameter, which are obtained by introducing a free variable to the lifting-based factorization of a Deslauriers–Dubuc interpolating filter. The exact one-parameter expressions for this class of IWTs are deduced and different IWTs can be easily obtained by adjusting the free parameter. In particular, several IWTs with their lifting filters all having binary coefficients are constructed. Extensive experiments show that our transforms have superior compression performance for both lossless and lossy image coding than the state-of-the-art IWTs, and yet require only comparable computational complexity. In addition, a quantization method that improves the rate-distortion performance of the IWT remarkably is also discussed.

Background/Objectives: The advancement of information exchange through internet has made it easy to transfer the exact information faster to the destination. Exchange the information safely to the destination with no alterations, there are many approaches like Cryptography, Steganography and Watermarking. Methods/Statistical Analysis: Steganography is a method of hiding a secret data in other cover medium. Digital Images are popular for cover medium than other because of their frequent use on the internet. In this paper a transform domain steganography with 9/7 Integer Wavelet Transform (IWT) is proposed. A pixel adaptive embedding method using LSB (Least Significant Bit) method is employed to increase the security of the secret data embedded in the a cover medium. Graph Theory is used to select the coefficients randomly for embedding the secret messages. Findings: It is found that the proposed method provides good security and high capacity. This algorithm can be applicable for all kinds of secret communications. Finally Results are compared with 5/3 IWT. Applications/Improvements: This method can be applied for all the secret communication applications especially Defence, Telemedicine, etc. This proposed method developed further in terms of robust against various steganalysis tools.

To achieve fast and secure information steganography in underwater acoustic channel scenarios, this paper proposes a PSO (Particle Swarm Optimization) and IWT (integer wavelet transform) based image steganography algorithm for underwater acoustic communication. Firstly, the underwater image to be embedded is interleaved and packed to generate the secret information code-stream to improve the detection and recovery performance of transmission errors. Secondly, the cover image is divided into non-overlapping blocks and IWT is applied to each block, which can save PSO search space and improve the optimal solution performance. Thirdly, the embedding position matrix of the high frequency sub-band coefficients is chaotic scrambled, and PSO is used to select the optimal key to obtain the optimal matching position for the secret information to produce the best stego-image quality. Finally, transmission error detection and recovery measures are applied to the extracted secret information to improve the reconstruction quality in underwater acoustic channel scenarios. Experimental results show that the proposed algorithm outperforms existing approaches in terms of information embedding capacity and steganographic visual quality, meeting the requirements of safety and real-time performance of underwater communication. Moreover, it also has the ability of error detection and recovery for harsh underwater acoustic channel.

The Integer Wavelet Transform (IWT) has proved particularly successful in the area of embedded lossy-to-lossless image coding. One of the possible methods to realize the IWT is the lifting scheme. Here we construct a new class of IWTs parameterized simply by one free parameter, which are obtained by introducing a free variable to the lifting based factorization of a Deslauriers-Dubuc interpolating filter. The exact one-parameter expressions for this class of IWTs are deduced and different IWT can be easily obtained by adjusting the free parameter. In particular, several IWTs with binary coefficients are constructed. Extensive experiments show, as compared with some state-of-the-art IWTs, that our transforms have more superior compression performance for both lossless and lossy image coding, and yet require only comparable computational complexity. Besides, a quantization method suitable for IWT is also discussed in this paper.KeywordsInteger Wavelet Transform (IWT)Lossy-to-lossless image codingLifting schemeCompression performanceComputational complexityQuantization

Image compression is a very important useful technique for efficient transmission as well as storage of images. The demand for communication of multimedia data through the telecommunication network and accessing the multimedia data through internet by utilizing less bandwidth for communication is growing explosively. Basically the image data comprise of significant portion of multimedia data and they occupy maximum portion of communication bandwidth for multimedia communication. Therefore the development of efficient image compression technique is quite necessary. The 2D Haar wavelet transform along with Hard Thresholding and Run Length Encoding is one of the efficient proposed image compression technique. JPEG2000 is a standard image compression method capable of producing very high quality compressed images. Conventional Run Length Encoding(CRLE),Optimized Run Length Encoding(ORLE),Enhanced Run Length Encoding(ERLE) are different types of RLES applied on both proposed method of compression and JPEG2000. Conventional Run Length Encoding produces efficient result for proposed method whereas Enhanced Run Length Encoding produces efficient result in JPEG2000 compression. This is the novel approach that the authors have proposed for compression of image using compression ratio (CR) without losing the PSNR, quality of image using lesser bandwidth.