The increasing popularity of the internet means that digital multimedia are transmitted more rapidly and easily. And people are very aware for media ownership. However, digital watermarking is an efficient and promising means to protect intellectual properties. Based on the intellectual property attention in the information era, how to protect the personal ownership is extremely important and a necessary scheme. In this paper, we propose an effective video watermarking method based on a pseudo-3-D discrete cosine transform (DCT) and quantization index modulation (QIM) against several attacks. The watermark is mainly inserted into the uncompressed domain by adjusting the correlation between DCT coefficients of the selected blocks, and the watermark extraction is blind. This approach consists of a pseudo-3-D DCT, watermark embedding, and extraction. A pseudo-3-D DCT, which is taken DCT transformation twice, will be first utilized to calculate the embedding factor and to obtain the useful messages. Using the QIM, we embed the watermark into the quantization regions from the successive raw frames in the uncompressed domain and record the relative information to create a secret embedding key. This secret embedding key will further apply to extraction. Experimental results demonstrate that the proposed method can survive filtering, compressions, luminance change, and noise attacks with a good invisibility and robustness.

A Video Watermarking Technique Based on Pseudo-3-D DCT and Quantization Index Modulation

Application of discrete transforms with selective coefficients for blind image watermarking

Digital watermarking techniques are used for the digital right managements and copyright protection. As known, it is a big deal in watermarking systems to make a good trade of between the robustness and imperceptibility. This paper presents a watermarking algorithm in the DCT domain using an evolutionary algorithm to satisfy both of robustness and imperceptibility. We employ a genetic-based algorithm to select pairs in DCT coefficients and insert watermark bit according to mathematical relation between selected coefficients in each 8×8 DCT block of image. The proposed method has been implemented and tested under various attacks including JPEG compression, additive noise distortion, and image filtering. The achieved results show that image remains imperceptible while the watermark survives the attacks especially in case of JPEG compression.

A Robust Evolutionary Based Digital Image Watermarking Technique in DCT Domain

In this paper, an efficient blind digital image watermarking algorithm using mapping technique is presented. The algorithm can embed or hide an entire image or pattern (logo) directly into the original image. The embedding process is based on changing the selected DCT coefficients of the host image to odd or even values depending on the binary bit value of watermark DCT coefficients. The algorithm is tested for fingerprint image embedded with a face watermark. It is demonstrated that the watermarking algorithm offers a significant advantage of providing biometric image compression and authentication without introducing any significant degradation in the image quality. Moreover the watermarking scheme is blind and does not require any additional data for logo extraction.

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A Blind DCT Domain Digital Watermarking for Biometric Authentication

One of the important applications of digital watermarking technology is copyright protection and ownership identification for digital images. To achieve this goal, robust watermarking has been rapidly developed in the past decade or so. Robust watermarking is designed to survive various non-geometric manipulations such as JPEG compression, additive noise and filtering as well as some geometric distortions such as rotation and scaling. In this chapter, the fundamental concept of digital watermarking, differences between visible and invisible watermarking, blind and non-blind watermark detection schemes, robust, fragile and semi-fragile watermarking algorithms, as well as four important properties for digital watermarking: imperceptibility, robustness, capacity and security will be described. A number of different transforms and algorithms used for robust image watermarking will be reviewed in detail. These include block based Discrete Cosine Transform (DCT), non-block based Discrete Wavelet Transform (DWT) and other state-of-the-art watermarking algorithms operating in the transform domain.

An Introduction to Robust Transform Based Image Watermarking Techniques

This paper deals with a new blind technique for robust image watermarking in the DCT domain. The technique is based on embedding watermark information in eight low-frequency band coefficients of the DCT sub-blocks. Single watermark has been embedded multi-times in the host image. The embedding process is based on changing the selected DCT-coefficients of the host image to odd or even values depending on the binary watermark's bit value. The proposed blind watermarking embedding has shown to be strongly robust against several attacks.

A New Blind Image Watermarking of Handwritten Signatures using Low-Frequency Band DCT Coefficients

This paper deals with a new blind robust watermarking technique for embedding two watermarks into a host image. The technique is based on embedding watermark information in sixteen low-frequency band coefficients of the DCT sub-blocks. The embedding process is based on changing the selected DCT-coefficients of the host image to odd or even values depending on the binary watermark's bit value. The proposed blind watermarking embedding has shown to be strongly robust against several attacks.

A New Blind Image Watermarking Technique for Dual Watermarks Using Low-Frequency Band DCT Coefficients

This paper presents a new design method for IIR notch filters with improved performance while operating with a limited number of samples. The design criterion is to minimize the error between the steady state and transient frequency responses while utilizing the initialization technique. The new filters which use multiple frequency initialization offer better transient frequency responses than conventional steady state filters with initialization.

Improved Transient Frequency Response of IIR Filters with Multiple Frequency Initialization

Remote sensing applications are nowadays widely spread in various industrial fields, such as mineral and water exploration, geo-structural mapping, and natural hazards analysis. These applications require that the performance of image processing tasks, such as segmentation, object detection, and classification, to be of high accuracy. This can be achieved with relative ease if the given image has high spatial resolution as well as high spectral resolution. However, due to sensor limitations, spatial and spectral resolutions have an inherently inverse relationship and cannot be achieved simultaneously. Hyperspectral Images (HSI) have high spectral resolution, but suffer from low spatial resolution, which hinders utilizing them to their full potential. One of the most widely used approaches to enhance spatial resolution is Single Image Super Resolution (SISR) techniques. In the recent years, Deep Convolutional Neural Networks (DCNNs) have been widely used for HSI enhancement, as they have shown superiority over other traditional methods. Nonetheless, researches still aspire to enhance HSI quality further while overcoming common challenges, such as spectral distortions. Research has shown that properties of natural images can be easily captured using complex numbers. However, this has not been thoroughly investigated from the perspective of HSI SISR. In this paper, we propose a variation of a Complex Valued Neural Network (CVNN) architecture for HSI spatial enhancement. The benefits of approaching the problem from a frequency domain perspective will be answered and the proposed network will be compared to its real counterpart and other state-of-the-art approaches. The evaluation and comparison will be recorded qualitatively by visual comparison, and quantitatively using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Spectral Angle Mapper (SAM).

Complex-valued neural network for hyperspectral single image super resolution

This paper introduces a new method for initializing a digital real second order IIR notch filter at two frequencies. It requires only the first received sample to initialize the filter's internal memories to their steady state values. The new method is suitable for filters used for detecting signals in the presence of strong clutter. The novelty of the new initialization lies in the fact that it does not change the implementation structure of the filter. Also, the new technique can operate in real time while offering similar performance to other techniques that require batch processing such as the projection initialization.

H. Al Ahmad

Papers

A New Blind Image Watermarking of Handwritten Signatures using Low-Frequency Band DCT Coefficients

A New Blind Image Watermarking Technique for Dual Watermarks Using Low-Frequency Band DCT Coefficients

Improved Transient Frequency Response of IIR Filters with Multiple Frequency Initialization

Complex-valued neural network for hyperspectral single image super resolution

A New Method for Initializing Real Second Order IIR Notch Filters