Sensei: Enforcing secure coding guidelines in the integrated development environment

We discuss the potential benefits, requirements, and implementation challenges of a security-by-design approach in which an integrated development environment plugin assists software developers to write code that complies with secure coding guidelines. We discuss how such a plugin can enable a company's policy-setting security experts and developers to pass their knowledge on to each other more efficiently, and to let developers more effectively put that knowledge into practice. This is achieved by letting the team members develop customized rule sets that formalize coding guidelines and by letting the plugin check the compliance of code being written to those rule sets in real time, similar to an as-you-type spell checker. Upon detected violations, the plugin suggests options to quickly fix them and offers additional information for the developer. We share our experience with proof-of-concept designs and implementations rolled out in multiple companies, and present some future research and development directions.     

3D holoscopic image coding scheme using HEVC with Gaussian process regression

3D holoscopic image, also known as integral imaging, light field imaging and plenoptic imaging, can provide a natural and fatigue-free 3D visualization. However, a large amount of data is required to represent the 3D holoscopic content. Therefore, efficient coding schemes for such particular type of image are needed. In this paper, we propose a Gaussian process regression based prediction scheme to compress the 3D holoscopic image. In the proposed scheme, the coding block and its prediction supports are modeled as a Gaussian process (GP) and Gaussian process regression (GPR) is used to obtain a better prediction of the coding block. Limited searching windows in horizontal and vertical directions are used to obtain the prediction supports, and a filtration method is designed to judge the reliability of the obtained prediction supports. Moreover, in order to alleviate the high complexity caused by GPR, a sparsification method is also put forward. Experimental results demonstrate the advantage of the proposed scheme for 3D holoscopic image coding in terms of different quality metrics as well as the visual quality of the views rendered from decompressed 3D holoscopic content, compared to the HEVC intra-prediction method and several other prediction methods in this field.     

Two-Phase Bidirectional Dual-Relay Selection Strategy for Wireless Relay Networks

In this article, we introduce a new bi-directional dual-relay selection strategy with its bit error rate (BER) performance analysis. During the first step of the proposed strategy, two relays out of a set of N relay-nodes are selected in a way to optimize the system performance in terms of BER, based on the suggested algorithm which checks if the selected relays using the max-min criterion are the best ones. In the second step, the chosen relay-nodes perform an orthogonal space-time coding scheme using the two-phase relaying protocol to establish a bi-directional communication between the communicating terminals, leading to a significant improvement in the achievable coding and diversity gain. To further improve the overall system performance, the selected relay-nodes apply also a digital network coding scheme. Furthermore, this paper discusses the analytical approximation of the BER performance of the proposed strategy, where we prove that the analytical results match almost perfectly the simulated ones. Finally, our simulation results show that the proposed strategy outperforms the current state-of-the-art ones.     

一种洗碗机溢水保护系统的设计

洗碗机溢水一般是指洗碗机进水过多,水溢出内胆底部而流到洗碗机底部钢板上。当溢出的水量超过底部钢板设定的蓄水容量时,洗碗机应发出报警信号及时切断进水,防止因进水过多而引起的事故。如果洗碗机溢水不能被检测和控制,由于洗碗机底部钢板盛水量有限,洗碗机溢出的水会从底部钢板流到地面上,会对地板、厨房甚至房屋造成极大的安全威胁,因此洗碗机具有安全可靠的溢水保护系统至关重要。     

Image denoising via sparse coding using eigenvectors of graph Laplacian

Image denoising plays an important role in image processing, which aims to separate clean images from the noisy images. A number of methods have been presented to deal with this practical problem in the past decades. In this paper, a sparse coding algorithm using eigenvectors of the graph Laplacian (EGL-SC) is proposed for image denoising by considering the global structures of images. To exploit the geometry attributes of images, the eigenvectors of the graph Laplacian, which are derived from the graph of noised patches, are incorporated in the sparse model as a set of basis functions. Sequently, the corresponding sparse coding problem is presented and efficiently solved with a relaxed iterative method in the framework of the double sparsity model. Meanwhile, as the denoising performance of the EGL-SC significantly depends on the number of the used eigenvectors, an optimal strategy for the number selection is employed. A parameter called as out-of-control rate is set to record the percentage of the denoised patches that suffer from serious residual errors in the sparse coding procedure. Thus, with the eigenvector number increasing, the appropriate number can be heuristically selected when the out-of-control rate falls below an empirical threshold. Experiments illustrate that the EGL-SC can achieve a better performance than some other well-developed denoising methods, especially in the structural similarity index for the noise of large deviations.     

Disparity-based just-noticeable-difference model for perceptual stereoscopic video coding using depth of focus blur effect

Human 3D perception provides an important clue to the removal of redundancy in stereoscopic 3D (S3D) videos. Because objects outside the binocular fusion limit cannot be fused on retina, the human visual system (HVS) makes them blur according to the depth-of-focus (DOF) effect to increase the binocular fusion limit and suppress diplopia, i.e. double vision. Based on human depth perception, we propose a disparity-based just-noticeable-difference model (DJND) to save bit-rate and improve visual comfort in S3D videos. We combine the DOF blur effect with conventional JND models in the pixel domain into DJND. Firstly, we use disparity information to get the average disparity value of each block. Then, we integrate the DOF blur effect into luminance JND (LJND) by a selective low pass Gaussian filter to minimize the visual stimulus in S3D videos. Finally, we incorporate disparity information into the filtered JND models to obtain DJND. Experimental results demonstrate that the proposed method successfully improves both image quality and visual comfort in viewing S3D videos without increasing the bit-rate.     

Syntactic compression codes at the zero entropy point

Syntactic compression codes compress the tree, which is the syntax of a binary source message. The ones considered here originate from image processing. The syntactic trees usedhave a constant valency and their binary labels distinguish whether the source substring derived from a node is completely zero or not. We compress them simply by deleting some redundant subtrees.

These codes fall into a theoretically new class of codes which is wider than the classical ones. They are here studied in the neighborhood of a zero of the binary entropy function. There, their behavior is close to that of an infinite run length encoding and the optimum valency is three. Finally, we open a problem, related with automata theory, which perhaps could provide a further link between Information Theory and Algorithmic Information Theory.     

面向自适应码流的渐进编码方法的研究

多媒体信息呈几何级数的爆炸性增长,带来海量信息的同时也带来庞大的数据量,加重了网络的负担,同时不同用户对所要接收图像的质量要求有所不同,如果以相同的标准进行处理势必会造成一定程度上信息的浪费。文章对静止图像的渐进编码作了进一步的研究,对基本层和增强层采用不同的编码策略,更加适应网络复杂多变的带宽条件。文章还通过与用户之间的交互式操作来满足用户不同的需求。实验结果表明,在压缩效果达到JPEG压缩标准的情况下,增强了渐进功能,更加适应网络需要。     

Lattice Vector Quantization Applied to Speech and Audio Coding

Lattice vector quantization(LVQ) has been used for real-time speech and audio coding systems.Compared with conventional vector quantization,LVQ has two main advantages:It has a simple and fast encoding process,and it significantly reduces the amount of memory required.Therefore,LVQ is suitable for use in low-complexity speech and audio coding.In this paper,we describe the basic concepts of LVQ and its advantages over conventional vector quantization.We also describe some LVQ techniques that have been used in speech and audio coding standards of international standards developing organizations(SDOs).