The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a...The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.展开更多
Due to the particularity of the seismic data, they must be treated by lossless compression algorithm in some cases. In the paper, based on the integer wavelet transform, the lossless compression algorithm is studied....Due to the particularity of the seismic data, they must be treated by lossless compression algorithm in some cases. In the paper, based on the integer wavelet transform, the lossless compression algorithm is studied. Comparing with the traditional algorithm, it can better improve the compression rate. CDF (2, n) biorthogonal wavelet family can lead to better compression ratio than other CDF family, SWE and CRF, which is owe to its capability in can- celing data redundancies and focusing data characteristics. CDF (2, n) family is suitable as the wavelet function of the lossless compression seismic data.展开更多
We study an approach to integer wavelet transform for lossless compression of medical image in medical picture archiving and communication system (PACS). By lifting scheme a reversible integer wavelet transform is gen...We study an approach to integer wavelet transform for lossless compression of medical image in medical picture archiving and communication system (PACS). By lifting scheme a reversible integer wavelet transform is generated, which has the similar features with the corresponding biorthogonal wavelet transform. Experimental results of the method based on integer wavelet transform are given to show better performance and great applicable potentiality in medical image compression.展开更多
Reversible data hiding is an information hiding technique that requires the retrieval of the error free cover image after the extraction of the secret image.We suggested a technique in this research that uses a recurs...Reversible data hiding is an information hiding technique that requires the retrieval of the error free cover image after the extraction of the secret image.We suggested a technique in this research that uses a recursive embedding method to increase capacity substantially using the Integer wavelet transform and the Arnold transform.The notion of Integer wavelet transforms is to ensure that all coefficients of the cover images are used during embedding with an increase in payload.By scrambling the cover image,Arnold transform adds security to the information that gets embedded and also allows embedding more information in each iteration.The hybrid combination of Integer wavelet transform and Arnold transform results to build a more efficient and secure system.The proposed method employs a set of keys to ensure that information cannot be decoded by an attacker.The experimental results show that it aids in the development of a more secure storage system and withstand few tampering attacks The suggested technique is tested on many image formats,including medical images.Various performance metrics proves that the retrieved cover image and hidden image are both intact.This System is proven to withstand rotation attack as well.展开更多
In view of the shortcomes of conventional ElectroCardioGram (ECG) compression algo- rithms,such as high complexity of operation and distortion of reconstructed signal,a new ECG compression encoding algorithm based on ...In view of the shortcomes of conventional ElectroCardioGram (ECG) compression algo- rithms,such as high complexity of operation and distortion of reconstructed signal,a new ECG compression encoding algorithm based on Set Partitioning In Hierarchical Trees (SPIHT) is brought out after studying the integer lifting scheme wavelet transform in detail.The proposed algorithm modifies zero-tree structure of SPIHT,establishes single dimensional wavelet coefficient tree of ECG signals and enhances the efficiency of SPIHT-encoding by distributing bits rationally,improving zero-tree set and ameliorating classifying method.For this improved algorithm,floating-point com- putation and storage are left out of consideration and it is easy to be implemented by hardware and software.Experimental results prove that the new algorithm has admirable features of low complexity, high speed and good performance in signal reconstruction.High compression ratio is obtained with high signal fidelity as well.展开更多
A floating-point wavelet-based and an integer wavelet-based image interpolations in lifting structures and polynomial curve fitting for image resolution enhancement are proposed in this paper. The proposed prediction ...A floating-point wavelet-based and an integer wavelet-based image interpolations in lifting structures and polynomial curve fitting for image resolution enhancement are proposed in this paper. The proposed prediction methods estimate high-frequency wavelet coefficients of the original image based on the available low-frequency wavelet coefficients, so that the original image can be reconstructed by using the proposed prediction method. To further improve the reconstruction performance, we use polynomial curve fitting to build relationships between actual high-frequency wavelet coefficients and estimated high-frequency wavelet coefficients. Results of the proposed prediction algorithm for different wavelet transforms are compared to show the proposed prediction algorithm outperforms other methods.展开更多
文摘The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.
文摘Due to the particularity of the seismic data, they must be treated by lossless compression algorithm in some cases. In the paper, based on the integer wavelet transform, the lossless compression algorithm is studied. Comparing with the traditional algorithm, it can better improve the compression rate. CDF (2, n) biorthogonal wavelet family can lead to better compression ratio than other CDF family, SWE and CRF, which is owe to its capability in can- celing data redundancies and focusing data characteristics. CDF (2, n) family is suitable as the wavelet function of the lossless compression seismic data.
文摘We study an approach to integer wavelet transform for lossless compression of medical image in medical picture archiving and communication system (PACS). By lifting scheme a reversible integer wavelet transform is generated, which has the similar features with the corresponding biorthogonal wavelet transform. Experimental results of the method based on integer wavelet transform are given to show better performance and great applicable potentiality in medical image compression.
文摘Reversible data hiding is an information hiding technique that requires the retrieval of the error free cover image after the extraction of the secret image.We suggested a technique in this research that uses a recursive embedding method to increase capacity substantially using the Integer wavelet transform and the Arnold transform.The notion of Integer wavelet transforms is to ensure that all coefficients of the cover images are used during embedding with an increase in payload.By scrambling the cover image,Arnold transform adds security to the information that gets embedded and also allows embedding more information in each iteration.The hybrid combination of Integer wavelet transform and Arnold transform results to build a more efficient and secure system.The proposed method employs a set of keys to ensure that information cannot be decoded by an attacker.The experimental results show that it aids in the development of a more secure storage system and withstand few tampering attacks The suggested technique is tested on many image formats,including medical images.Various performance metrics proves that the retrieved cover image and hidden image are both intact.This System is proven to withstand rotation attack as well.
文摘In view of the shortcomes of conventional ElectroCardioGram (ECG) compression algo- rithms,such as high complexity of operation and distortion of reconstructed signal,a new ECG compression encoding algorithm based on Set Partitioning In Hierarchical Trees (SPIHT) is brought out after studying the integer lifting scheme wavelet transform in detail.The proposed algorithm modifies zero-tree structure of SPIHT,establishes single dimensional wavelet coefficient tree of ECG signals and enhances the efficiency of SPIHT-encoding by distributing bits rationally,improving zero-tree set and ameliorating classifying method.For this improved algorithm,floating-point com- putation and storage are left out of consideration and it is easy to be implemented by hardware and software.Experimental results prove that the new algorithm has admirable features of low complexity, high speed and good performance in signal reconstruction.High compression ratio is obtained with high signal fidelity as well.
文摘A floating-point wavelet-based and an integer wavelet-based image interpolations in lifting structures and polynomial curve fitting for image resolution enhancement are proposed in this paper. The proposed prediction methods estimate high-frequency wavelet coefficients of the original image based on the available low-frequency wavelet coefficients, so that the original image can be reconstructed by using the proposed prediction method. To further improve the reconstruction performance, we use polynomial curve fitting to build relationships between actual high-frequency wavelet coefficients and estimated high-frequency wavelet coefficients. Results of the proposed prediction algorithm for different wavelet transforms are compared to show the proposed prediction algorithm outperforms other methods.
