Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

A Watermarking Algorithm Based on DCT and JPEG Quantization Table

In this paper, we propose a scheme of watermark embedding and extracting based on DCT transform and JPEG quantization table. Firstly, the image is divided into non-overlapping 8 × 8 blocks, and each block is transformed by DCT. Then, a pair of points with the same quantization value is selected by the JPEG quantization table in order to embed one watermark bit, and the adjustment coefficients are adaptively selected by using the visual masking property of HVS. The experimental results presented in this paper showed that our proposed algorithm is robust to JPEG compression under different quality factors

Steganography: a class of secure and robust algorithms

This research work presents a new class of non-blind information hiding algorithms that are stego-secure and robust. They are based on some finite domains iterations having the Devaney's topological chaos property. Thanks to a complete formalization of the approach we prove security against watermark-only attacks of a large class of steganographic algorithms. Finally a complete study of robustness is given in frequency DWT and DCT domains.Comment: Published in The Computer Journal special issue about steganograph

Noise- and compression-robust biological features for texture classification

Texture classification is an important aspect of many digital image processing applications such as surface inspection, content-based image retrieval, and biomedical image analysis. However, noise and compression artifacts in images cause problems for most texture analysis methods. This paper proposes the use of features based on the human visual system for texture classification using a semisupervised, hierarchical approach. The texture feature consists of responses of cells which are found in the visual cortex of higher primates. Classification experiments on different texture libraries indicate that the proposed features obtain a very high classification near 97%. In contrast to other well-established texture analysis methods, the experiments indicate that the proposed features are more robust to various levels of speckle and Gaussian noise. Furthermore, we show that the classification rate of the textures using the presented biologically inspired features is hardly affected by image compression techniques

Spread spectrum-based video watermarking algorithms for copyright protection

Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen

An Adaptive Spread Spectrum (SS) Synchronous Data Hiding Strategy for Scalable 3D Terrain Visualization

International audienceThe diversity of clients in today's network environment compels us to think about solutions that more than satisfy their needs according to their resources. For 3D terrain visualization this translates into two main requirements, namely the scalability and synchronous unification of a disparate data that requires at least two files, the texture image and its corresponding digital elevation model (DEM). In this work the scalability is achieved through the multiresolution discrete wavelet transform (DWT) of the JPEG2000 codec. For the unification of data, a simple DWT-domain spread spectrum (SS) strategy is employed in order to synchronously hide the DEM in the corresponding texture while conserving the JPEG2000 standard file format. Highest possible quality texture is renderable due to the reversible nature of the SS data hiding. As far as DEM quality is concerned, it is ensured through the adaptation of synchronization in embedding that would exclude some highest frequency subbands. To estimate the maximum tolerable error in the DEM according to a given viewpoint, a human visual system (HVS) based psycho-visual analysis is being presented. This analysis is helpful in determining the degree of adaptation in synchronization

Space-optimized texture atlases

Texture atlas parameterization provides an effective way to map a variety of colour and data attributes from 2D texture domains onto polygonal surface meshes. Most of the existing literature focus on how to build seamless texture atlases for continuous photometric detail, but little e ort has been devoted to devise e cient techniques for encoding self-repeating, uncontinuous signals such as building facades. We present a perception-based scheme for generating space-optimized texture atlases speci cally designed for intentionally non-bijective parameterizations. Our scheme combines within-chart tiling support with intelligent packing and perceptual measures for assigning texture space in accordance to the amount of information contents of the image and on its saliency. We demonstrate our optimization scheme in the context of real-time navigation through a gigatexel urban model of an European city. Our scheme achieves signi cant compression ratios and speed-up factors with visually indistinguishable results. We developed a technique that generates space-optimized texture atlases for the particular encoding of uncontinuous signals projected onto geometry. The scene is partitioned using a texture atlas tree that contains for each node a texture atlas. The leaf nodes of the tree contain scene geometry. The level of detail is controlled by traversing the tree and selecting the appropriate texture atlas for a given viewer position and orientation. In a preprocessing step, textures associated to each texture atlas node of the tree are packed. Textures are resized according to a given user-de ned texel size and the size of the geometry that are projected onto. We also use perceptual measures to assign texture space in accordance to image detail. We also explore different techniques for supporting texture wrapping of uncontinuous signals, which involved the development of e cient techniques for compressing texture coordinates via the GPU. Our approach supports texture ltering and DXTC compression without noticeable artifacts. We have implemented a prototype version of our space-optimized texture atlases technique and used it to render the 3D city model of Barcelona achieving interactive rendering frame rates. The whole model was composed by more than three million triangles and contained more than twenty thousand different textures representing the building facades with an average original resolution of 512 pixels per texture. Our scheme achieves up 100:1 compression ratios and speed-up factors of 20 with visually indistinguishable results