Iman M . G . Alwan | University of Baghdad (original) (raw)

Papers by Iman M . G . Alwan

Research paper thumbnail of Digital Image Watermarking Using Arnold Scrambling and Berkeley Wavelet Transform

Embedding an identifying data into digital media such as video, audio or image is known as digita... more Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

Research paper thumbnail of Multi-Focus Image Fusion Using Discrete Cosine Harmonic Wavelet Transform

Multi-focus image fusion algorithms are used to combine a collection of different focuses images ... more Multi-focus image fusion algorithms are used to combine a collection of different focuses images that represent the same scene, to produce a sharper one. In this paper, a transform domain multi-focus image fusion algorithm is proposed. It depends on using Discrete Cosine Harmonic Wavelet Transform and pixel-based rule of fusion. Region entropy is used to fuse coefficients of approximation subbands, while maximum rule with consistency verification is utilized in fusion of detail subbands of the Discrete Cosine Harmonic Wavelet Transform domain. The fused resultant image is obtained by applying inverse Discrete Cosine Harmonic Wavelet Transform to the combined coefficients.The proposed method is compared with several transform domain based fusion algorithms, and it shows better performance or similar performance under several objective criteria.

Research paper thumbnail of Watermarking in Image Using Slantlet Transform

A watermarking scheme based on slantlet transform, an orthogonal discrete wavelet transform with ... more A watermarking scheme based on slantlet transform, an orthogonal discrete wavelet transform with two zero moments and with improved time localization, is presented in this paper. The watermark is embedded into mid band frequencies of slantlet coefficients in the transform domain, which leads to very small distortion and guarantees the visual quality of the watermarked image. The performance of the proposed algorithm is compared with embedding watermarking system using wavelet transformation the result show promising performance of the proposed system where the increasing in PSNR is approximately 20 dB.

Research paper thumbnail of Hybrid Transform Based Denoising with Block Thresholding

Research paper thumbnail of Al-Khwarizmi Engineering Journal Color Image Denoising Using Stationary Wavelet Transform and Adaptive Wiener Filter

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image proc... more The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing. Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds. This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by using MATLAB R2010a with color images contaminated by white Gaussian noise. Compared with stationary wavelet and wiener filter algorithms, the experimental results show that the proposed method provides better subjective and objective quality, and obtain up to 3.5 dB PSNR improvement.

Research paper thumbnail of Image Steganography by Using Multiwavelet Transform

Steganography is the art of secret communication. Its purpose is to hide the presence of informat... more Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors α and β in frequency domain control the quality of the stego images. The proposed algorithm is compared with wavelet based algorithm which shows a favorable results in terms of PSNR reaches to 18 dB.

Research paper thumbnail of Digital Image Watermarking Using Arnold Scrambling and Berkeley Wavelet Transform

Embedding an identifying data into digital media such as video, audio or image is known as digita... more Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

Research paper thumbnail of Multi-Focus Image Fusion Using Discrete Cosine Harmonic Wavelet Transform

Multi-focus image fusion algorithms are used to combine a collection of different focuses images ... more Multi-focus image fusion algorithms are used to combine a collection of different focuses images that represent the same scene, to produce a sharper one. In this paper, a transform domain multi-focus image fusion algorithm is proposed. It depends on using Discrete Cosine Harmonic Wavelet Transform and pixel-based rule of fusion. Region entropy is used to fuse coefficients of approximation subbands, while maximum rule with consistency verification is utilized in fusion of detail subbands of the Discrete Cosine Harmonic Wavelet Transform domain. The fused resultant image is obtained by applying inverse Discrete Cosine Harmonic Wavelet Transform to the combined coefficients.The proposed method is compared with several transform domain based fusion algorithms, and it shows better performance or similar performance under several objective criteria.

Research paper thumbnail of Watermarking in Image Using Slantlet Transform

A watermarking scheme based on slantlet transform, an orthogonal discrete wavelet transform with ... more A watermarking scheme based on slantlet transform, an orthogonal discrete wavelet transform with two zero moments and with improved time localization, is presented in this paper. The watermark is embedded into mid band frequencies of slantlet coefficients in the transform domain, which leads to very small distortion and guarantees the visual quality of the watermarked image. The performance of the proposed algorithm is compared with embedding watermarking system using wavelet transformation the result show promising performance of the proposed system where the increasing in PSNR is approximately 20 dB.

Research paper thumbnail of Hybrid Transform Based Denoising with Block Thresholding

Research paper thumbnail of Al-Khwarizmi Engineering Journal Color Image Denoising Using Stationary Wavelet Transform and Adaptive Wiener Filter

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image proc... more The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing. Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds. This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by using MATLAB R2010a with color images contaminated by white Gaussian noise. Compared with stationary wavelet and wiener filter algorithms, the experimental results show that the proposed method provides better subjective and objective quality, and obtain up to 3.5 dB PSNR improvement.

Research paper thumbnail of Image Steganography by Using Multiwavelet Transform

Steganography is the art of secret communication. Its purpose is to hide the presence of informat... more Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors α and β in frequency domain control the quality of the stego images. The proposed algorithm is compared with wavelet based algorithm which shows a favorable results in terms of PSNR reaches to 18 dB.