PSO Based Lossless and Robust Image Watermarking using Integer Wavelet Transform

In recent days, the advances in the broadcasting of multimedia contents in digital format motivate to protect this digital multimedia content form illegal use, such as manipulation, duplication and redistribution. However, watermarking algorithms are designed to meet the requirements of different applications, because, various applications have various requirements. This paper intends to design a new watermarking algorithm with an aim of provision of a tradeoff between the robustness and imperceptibility and also to reduce the information loss. This approach applies Integer Wavelet Transform (IWT) instead of conventional floating point wavelet transforms which are having main drawback of round of error. Then the most popular artificial intelligence technique, particle swarm optimization (PSO) used for optimization of watermarking strength. The strength of watermarking technique is directly related to the watermarking constant alpha. The PSO optimizes alpha values such that, the proposed approach achieves better robustness over various attacks and an also efficient imperceptibility. Numerous experiments are conducted over the proposed approach to evaluate the performance. The obtained experimental results demonstrates that the proposed approach is superior compared to conventional approach and is able to provide efficient resistance over Gaussian noise, sal

A Study in Image Watermarking Schemes using Neural Networks

The digital watermarking technique, an effective way to protect image, has become the research focus on neural network. The purpose of this paper is to provide a brief study on broad theories and discuss the different types of neural networks for image watermarking. Most of the research interest image watermarking based on neural network in discrete wavelet transform or discrete cosine transform. Generally image watermarking based on neural network to solve the problem on to reduce the error, improve the rate of the learning, achieves goods imperceptibility and robustness. It will be useful for researches to implement effective image watermarking by using neural network

A NOVEL APPROACH IN IMAGE WATERMARKING WITH DISCRETE WAVELET TRANSFORM

In this paper we present a new watermarking scheme for still image data. Most of the recent work in watermarking can be grouped into two categories: spatial domain methods and frequency domain methods. We introduce a novel approach of watermarking which involves embedding the watermark in the discrete wavelet domain. We make use of a multi resolution data fusion approach in which the image and watermark are both transformed into the discrete wavelet domain. The resulting image pyramids are then fused according to a series of combination. After watermark insertion, inverse DWT is applied to the sub-bands with modified coefficients to obtain the watermarked image. For watermark extraction, a threshold-based decoder is designed. Embedding and extraction process are characterized with parameters and genetic algorithm is used for parameter optimization. Optimization is to maximize the values of peak signal-to-noise ratio of the watermarked image and normalized cross correlation of the extracted watermark. The performance of the proposed scheme is compared with the existing schemes and significant improvement is observed

Quantization Watermarking for Joint Compression and Data Hiding Schemes

International audienceEnrichment and protection of JPEG2000 images is an important issue. Data hiding techniques are a good solution to solve these problems. In this context, we can consider the joint approach to introduce data hiding technique into JPEG2000 coding pipeline. Data hiding consists of imperceptibly altering multimedia content, to convey some information. This process is done in such a way that the hidden data is not perceptible to an observer. Digital watermarking is one type of data hiding. In addition to the imperceptibility and payload constraints, the watermark should be robust against a variety of manipulations or attacks. We focus on trellis coded quantization (TCQ) data hiding techniques and propose two JPEG2000 compression and data hiding schemes. The properties of TCQ quantization, defined in JPEG2000 part 2, are used to perform quantization and information embedding during the same time. The first scheme is designed for content description and management applications with the objective of achieving high payloads. The compression rate/imperceptibility/payload trade off is our main concern. The second joint scheme has been developed for robust watermarking and can have consequently many applications. We achieve the better imperceptibility/robustness trade off in the context of JPEG2000 compression. We provide some experimental results on the implementation of these two schemes