The Experts below are selected from a list of 3741 Experts worldwide ranked by ideXlab platform
Gholamreza Anbarjafari - One of the best experts on this subject based on the ideXlab platform.
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A watermarking algorithm based on chirp z-transform, discrete wavelet transform, and singular value decomposition
Signal Image and Video Processing, 2015Co-Authors: Mary Agoyi, Erbuğ Çelebi, Gholamreza AnbarjafariAbstract:Digital watermarking has attracted increasing attentions as it has been the current solution to copyright protection and content authentication which has become an issue to be addressed in multimedia technology. This study introduces a novel watermarking scheme based on the discrete wavelet transform (DWT) in combination with the chirp z-transform (CZT) and the singular value decomposition (SVD). Firstly, the image is decomposed into its Frequency Subbands by using 1-level DWT. Then, the high-Frequency subband is transformed into z-domain by using CZT. Afterward by SVD, the watermark is added to the singular matrix of the transformed image. Finally, the watermarked image is obtained by using inverse of CZT and inverse of DWT. This algorithm combines the advantages of all three algorithms. The experimental result shows that the algorithm is imperceptible and robust to several attacks and signal processing operations.
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discrete wavelet transform based satellite image resolution enhancement
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:Satellite images are being used in many fields of research. One of the major issues of these types of images is their resolution. In this paper, we propose a new satellite image resolution enhancement technique based on the interpolation of the high-Frequency Subbands obtained by discrete wavelet transform (DWT) and the input image. The proposed resolution enhancement technique uses DWT to decompose the input image into different Subbands. Then, the high-Frequency subband images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new resolution-enhanced image by using inverse DWT. In order to achieve a sharper image, an intermediate stage for estimating the high-Frequency Subbands has been proposed. The proposed technique has been tested on satellite benchmark images. The quantitative (peak signal-to-noise ratio and root mean square error) and visual results show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques.
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IMAGE Resolution Enhancement by Using Discrete and Stationary Wavelet Decomposition
IEEE Transactions on Image Processing, 2011Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:In this correspondence, the authors propose an image resolution enhancement technique based on interpolation of the high Frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input image into different Subbands. Then the high Frequency Subbands as well as the input image are interpolated. The estimated high Frequency Subbands are being modified by using high Frequency subband obtained through SWT. Then all these Subbands are combined to generate a new high resolution image by using inverse DWT (IDWT). The quantitative and visual results are showing the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques.
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image super resolution based on interpolation of wavelet domain high Frequency Subbands and the spatial domain input image
Etri Journal, 2010Co-Authors: Gholamreza Anbarjafari, Hasan DemirelAbstract:In this paper, we propose a new super-resolution technique based on interpolation of the high-Frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The proposed technique uses DWT to decompose an image into different subband images. Then the high-Frequency subband images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new super-resolved image by using inverse DWT. The proposed technique has been tested on Lena, Elaine, Pepper, and Baboon. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques. For Lena's image, the PSNR is 7.93 dB higher than the bicubic interpolation.
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satellite image contrast enhancement using discrete wavelet transform and singular value decomposition
IEEE Geoscience and Remote Sensing Letters, 2010Co-Authors: Hasan Demirel, Cagri Ozcinar, Gholamreza AnbarjafariAbstract:In this letter, a new satellite image contrast enhancement technique based on the discrete wavelet transform (DWT) and singular value decomposition has been proposed. The technique decomposes the input image into the four Frequency Subbands by using DWT and estimates the singular value matrix of the low-low subband image, and, then, it reconstructs the enhanced image by applying inverse DWT. The technique is compared with conventional image equalization techniques such as standard general histogram equalization and local histogram equalization, as well as state-of-the-art techniques such as brightness preserving dynamic histogram equalization and singular value equalization. The experimental results show the superiority of the proposed method over conventional and state-of-the-art techniques.
Hasan Demirel - One of the best experts on this subject based on the ideXlab platform.
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discrete wavelet transform based satellite image resolution enhancement
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:Satellite images are being used in many fields of research. One of the major issues of these types of images is their resolution. In this paper, we propose a new satellite image resolution enhancement technique based on the interpolation of the high-Frequency Subbands obtained by discrete wavelet transform (DWT) and the input image. The proposed resolution enhancement technique uses DWT to decompose the input image into different Subbands. Then, the high-Frequency subband images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new resolution-enhanced image by using inverse DWT. In order to achieve a sharper image, an intermediate stage for estimating the high-Frequency Subbands has been proposed. The proposed technique has been tested on satellite benchmark images. The quantitative (peak signal-to-noise ratio and root mean square error) and visual results show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques.
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IMAGE Resolution Enhancement by Using Discrete and Stationary Wavelet Decomposition
IEEE Transactions on Image Processing, 2011Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:In this correspondence, the authors propose an image resolution enhancement technique based on interpolation of the high Frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input image into different Subbands. Then the high Frequency Subbands as well as the input image are interpolated. The estimated high Frequency Subbands are being modified by using high Frequency subband obtained through SWT. Then all these Subbands are combined to generate a new high resolution image by using inverse DWT (IDWT). The quantitative and visual results are showing the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques.
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image super resolution based on interpolation of wavelet domain high Frequency Subbands and the spatial domain input image
Etri Journal, 2010Co-Authors: Gholamreza Anbarjafari, Hasan DemirelAbstract:In this paper, we propose a new super-resolution technique based on interpolation of the high-Frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The proposed technique uses DWT to decompose an image into different subband images. Then the high-Frequency subband images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new super-resolved image by using inverse DWT. The proposed technique has been tested on Lena, Elaine, Pepper, and Baboon. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques. For Lena's image, the PSNR is 7.93 dB higher than the bicubic interpolation.
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satellite image contrast enhancement using discrete wavelet transform and singular value decomposition
IEEE Geoscience and Remote Sensing Letters, 2010Co-Authors: Hasan Demirel, Cagri Ozcinar, Gholamreza AnbarjafariAbstract:In this letter, a new satellite image contrast enhancement technique based on the discrete wavelet transform (DWT) and singular value decomposition has been proposed. The technique decomposes the input image into the four Frequency Subbands by using DWT and estimates the singular value matrix of the low-low subband image, and, then, it reconstructs the enhanced image by applying inverse DWT. The technique is compared with conventional image equalization techniques such as standard general histogram equalization and local histogram equalization, as well as state-of-the-art techniques such as brightness preserving dynamic histogram equalization and singular value equalization. The experimental results show the superiority of the proposed method over conventional and state-of-the-art techniques.
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Satellite Image Resolution Enhancement Using Complex Wavelet Transform
IEEE Geoscience and Remote Sensing Letters, 2010Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:In this letter, a satellite image resolution enhancement technique based on interpolation of the high-Frequency subband images obtained by dual-tree complex wavelet transform (DT-CWT) is proposed. DT-CWT is used to decompose an input low-resolution satellite image into different Subbands. Then, the high-Frequency subband images and the input image are interpolated, followed by combining all these images to generate a new high-resolution image by using inverse DT-CWT. The resolution enhancement is achieved by using directional selectivity provided by the CWT, where the high-Frequency Subbands in six different directions contribute to the sharpness of the high-Frequency details such as edges. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional bicubic interpolation, wavelet zero padding, and Irani and Peleg based image resolution enhancement techniques.
Yun Q Shi - One of the best experts on this subject based on the ideXlab platform.
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lossless data hiding using histogram shifting method based on integer wavelets
Lecture Notes in Computer Science, 2006Co-Authors: Guorong Xuan, Chengyun Yang, Qiuming Yao, Jianjiong Gao, Peiqi Chai, Yun Q ShiAbstract:This paper 1 proposes a histogram shifting method for image lossless data hiding in integer wavelet transform domain. This algorithm hides data into wavelet coefficients of high Frequency Subbands. It shifts a part of the histogram of high Frequency wavelet Subbands and thus embeds data by using the created histogram zero-point. This shifting process may be sequentially carried out if necessary. Histogram modification technique is applied to prevent overflow and underflow. The performance of this proposed technique in terms of the data embedding payload versus the visual quality of marked images is compared with that of the existing lossless data hiding methods implemented in the spatial domain, integer cosine transform domain, and integer wavelet transform domain. The experimental results have demonstrated the superiority of the proposed method over the existing methods. That is, the proposed method has a larger embedding payload in the same visual quality (measured by PSNR (peak signal noise ratio)) or has a higher PSNR in the same payload.
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reversible data hiding using integer wavelet transform and companding technique
International Workshop on Digital Watermarking, 2004Co-Authors: Guorong Xuan, Chengyun Yang, Yizhan Zhen, Yun Q ShiAbstract:This paper presents a novel reversible data-embedding method for digital images using integer wavelet transform and companding technique. This scheme takes advantage of the Laplacian-like distribution of integer wavelet coefficients in high Frequency Subbands, which facilitates the selection of compression and expansion functions and keeps the distortion small between the marked image and the original one. Experimental results show that this scheme outperforms the state-of-the-art reversible data hiding schemes.
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lossless data hiding based on integer wavelet transform
Multimedia Signal Processing, 2002Co-Authors: Guorong Xuan, Jidong Chen, Jiang Zhu, Yun Q ShiAbstract:This paper proposes a novel data hiding algorithm having large data hiding rate based on integer wavelet transform, which can recover the original image without any distortion from the marked image after the hidden data have been extracted. This algorithm hides the data and the overhead data representing the bookkeeping information into the middle bit-plane of the integer wavelet coefficients in high Frequency Subbands. It can embed much more data compared with the existing distortionless data hiding techniques and satisfy the imperceptibility requirement. The image histogram modification is used to prevent grayscales from possible overflowing that may take place due to the data embedding. The algorithm has been applied to a wide range of different images successfully. Some experimental results are presented in this paper to demonstrate the validity of the algorithm.
Guorong Xuan - One of the best experts on this subject based on the ideXlab platform.
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lossless data hiding using histogram shifting method based on integer wavelets
Lecture Notes in Computer Science, 2006Co-Authors: Guorong Xuan, Chengyun Yang, Qiuming Yao, Jianjiong Gao, Peiqi Chai, Yun Q ShiAbstract:This paper 1 proposes a histogram shifting method for image lossless data hiding in integer wavelet transform domain. This algorithm hides data into wavelet coefficients of high Frequency Subbands. It shifts a part of the histogram of high Frequency wavelet Subbands and thus embeds data by using the created histogram zero-point. This shifting process may be sequentially carried out if necessary. Histogram modification technique is applied to prevent overflow and underflow. The performance of this proposed technique in terms of the data embedding payload versus the visual quality of marked images is compared with that of the existing lossless data hiding methods implemented in the spatial domain, integer cosine transform domain, and integer wavelet transform domain. The experimental results have demonstrated the superiority of the proposed method over the existing methods. That is, the proposed method has a larger embedding payload in the same visual quality (measured by PSNR (peak signal noise ratio)) or has a higher PSNR in the same payload.
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reversible data hiding using integer wavelet transform and companding technique
International Workshop on Digital Watermarking, 2004Co-Authors: Guorong Xuan, Chengyun Yang, Yizhan Zhen, Yun Q ShiAbstract:This paper presents a novel reversible data-embedding method for digital images using integer wavelet transform and companding technique. This scheme takes advantage of the Laplacian-like distribution of integer wavelet coefficients in high Frequency Subbands, which facilitates the selection of compression and expansion functions and keeps the distortion small between the marked image and the original one. Experimental results show that this scheme outperforms the state-of-the-art reversible data hiding schemes.
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distortionless data hiding based on integer wavelet transform
Electronics Letters, 2002Co-Authors: Guorong Xuan, Jidong Chen, Zhicheng Ni, Wei SuAbstract:A novel distortionless image data hiding algorithm based on integer wavelet transform that can invert the stego-image into the original image without any distortion after the hidden data are extracted is proposed. This algorithm hides data into one (or more) middle bit-plane(s) of the integer wavelet transform coefficients in the middle and high Frequency Subbands. It can embed much more data compared with the existing distortionless data hiding techniques and satisfy the imperceptibility requirement. The image histogram modification is used to prevent greyscales from possible overflowing. Experimental results have demonstrated the validity of the algorithm.
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lossless data hiding based on integer wavelet transform
Multimedia Signal Processing, 2002Co-Authors: Guorong Xuan, Jidong Chen, Jiang Zhu, Yun Q ShiAbstract:This paper proposes a novel data hiding algorithm having large data hiding rate based on integer wavelet transform, which can recover the original image without any distortion from the marked image after the hidden data have been extracted. This algorithm hides the data and the overhead data representing the bookkeeping information into the middle bit-plane of the integer wavelet coefficients in high Frequency Subbands. It can embed much more data compared with the existing distortionless data hiding techniques and satisfy the imperceptibility requirement. The image histogram modification is used to prevent grayscales from possible overflowing that may take place due to the data embedding. The algorithm has been applied to a wide range of different images successfully. Some experimental results are presented in this paper to demonstrate the validity of the algorithm.
M Ghanbari - One of the best experts on this subject based on the ideXlab platform.
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efficient algorithm for very low bit rate embedded image coding
Iet Image Processing, 2008Co-Authors: Athar Ali Moinuddin, Ekram Khan, M GhanbariAbstract:The authors propose an embedded wavelet-based image coding algorithm that exploits both the inter- and intra-subband correlations among the wavelet coefficients. The proposed coding algorithm is based on spatial orientation trees (SOT) in which the basic unit is a block of m times n coefficients in contrast to a single coefficient in the set partitioning in hierarchical trees (SPIHT) algorithm. Each SOT has a root node (a block of m times n coefficients) in the LL-subband with the child and descendent blocks in the high Frequency Subbands. Thus it fuses the features of both block- and tree-based coding algorithms into a single algorithm. Performance of the proposed method is compared (in terms of rate-distortion performance) with the other state-of-the-art coding algorithms including the JPEG2000 for popular test images. Simulation results show that the proposed algorithm has a better coding efficiency over the other coders at very low bit rates. Also, compared with SPIHT it reduces the elements of the auxiliary lists, thereby reducing the memory requirements. In addition, the encoder of the proposed algorithm is significantly faster than that of the SPIHT, but with a slight increase in its decoder complexity.
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reversible date hiding using multi level integer wavelet decomposition and intelligent coefficient selection
International Conference on Multimedia and Expo, 2007Co-Authors: Safoora Yousefi, Hamid R Rabiee, E Yousefi, M GhanbariAbstract:This paper presents a lossless data hiding method using coefficients of integer wavelet domain. The modification of selected small coefficients of the high Frequency Subbands are used to embed data. We use the histogram modification to intelligently select the proper coefficients for data hiding. Data embedding is done by processing these selected coefficients. We show that at low payload data hiding our method has comparable PSNR than the best known reversible data hiding techniques, while at higher payloads it has significant superiority on image quality.
