Releasing aperture filter constraints

Aperture filters are a recently introduced class of nonlinear filters used in image processing. In this paper we present a new approach for aperture filter design, improving operator performance with respect to the MSE measure by releasing some of the operator constraints without losing statistical estimation accuracy. With the use of the proposed methods an average of 34% MSE reduction was achieved for deblurring, whereas a standard aperture operator reduced the error by only 10% on the average

Coverage and density of a low power, low data rate, spread spectrum wireless sensor network for agricultural monitoring

A physical layer specification for a low power, low complexity, low data rate sensor network suitable for agricultural monitoring is investigated. Code division multiple access (CDMA) with high processing gain is used to facilitate transmission powers which comply with the Ultra Wide Band (UWB) spectral mask, and this permits physically small nodes with limited energy storage capacity. The interference arising from each node is calculated, and it is shown that for the investigated scenario and specification, an aggregate data rate of 2 bytes per minute and a node population of approximately 1000 can be supported at distances up to a few kilometres from the central node, with less than 0.2% chance of failure due to multiple access interference

Source localization in shallow ocean using a vertical array of acoustic vector sensors

This paper introduces a new approach to 3D localisation of a narrowband acoustic source in a shallow ocean using acoustic vector sensors (AVS). Assuming a horizontally stratified and range-independent model of the ocean, it is shown that the azimuth of the source can be determined from the estimates of the horizontal components of the acoustic intensity vector obtained from the measurements of an AVS. The range and depth of the source could then be estimated through a 2D search to match the computed complex acoustic intensity vector expressed as a function of these parameters with its estimate obtained from the AVS measurements. However the search in range is computationally intensive as the range parameter is unbounded. We propose an alternative approach employing a vertical array of AVS, based on eigen-decomposition of the spatial correlation matrix of the data vector, leading to a closed form solution for the range parameter. The source depth is then estimated through a 1D search of this bounded parameter

Locally Adaptive Resolution (LAR) codec

The JPEG committee has initiated a study of potential technologies dedicated to future generation image compression systems. The idea is to design a new norm of image compression, named JPEG AIC (Advanced Image Coding), together with advanced evaluation methodologies, closely matching to human vision system characteristics. JPEG AIC thus aimed at defining a complete coding system able to address advanced functionalities such as lossy to lossless compression, scalability (spatial, temporal, depth, quality, complexity, component, granularity...), robustness, embed-ability, content description for image handling at object level... The chosen compression method would have to fit perceptual metrics defined by the JPEG community within the JPEG AIC project. In this context, we propose the Locally Adaptive Resolution (LAR) codec as a contribution to the relative call for technologies, tending to fit all of previous functionalities. This method is a coding solution that simultaneously proposes a relevant representation of the image. This property is exploited through various complementary coding schemes in order to design a highly scalable encoder. The LAR method has been initially introduced for lossy image coding. This efficient image compression solution relies on a content-based system driven by a specific quadtree representation, based on the assumption that an image can be represented as layers of basic information and local texture. Multiresolution versions of this codec have shown their efficiency, from low bit rates up to lossless compressed images. An original hierarchical self-extracting region representation has also been elaborated: a segmentation process is realized at both coder and decoder, leading to a free segmentation map. This later can be further exploited for color region encoding, image handling at region level. Moreover, the inherent structure of the LAR codec can be used for advanced functionalities such as content securization purposes. In particular, dedicated Unequal Error Protection systems have been produced and tested for transmission over the Internet or wireless channels. Hierarchical selective encryption techniques have been adapted to our coding scheme. Data hiding system based on the LAR multiresolution description allows efficient content protection. Thanks to the modularity of our coding scheme, complexity can be adjusted to address various embedded systems. For example, basic version of the LAR coder has been implemented onto FPGA platform while respecting real-time constraints. Pyramidal LAR solution and hierarchical segmentation process have also been prototyped on DSPs heterogeneous architectures. This chapter first introduces JPEG AIC scope and details associated requirements. Then we develop the technical features, of the LAR system, and show the originality of the proposed scheme, both in terms of functionalities and services. In particular, we show that the LAR coder remains efficient for natural images, medical images, and art images

Complex and Hypercomplex Discrete Fourier Transforms Based on Matrix Exponential Form of Euler's Formula

We show that the discrete complex, and numerous hypercomplex, Fourier transforms defined and used so far by a number of researchers can be unified into a single framework based on a matrix exponential version of Euler's formula $e^{j\theta}=\cos\theta+j\sin\theta$, and a matrix root of -1 isomorphic to the imaginary root $j$. The transforms thus defined can be computed using standard matrix multiplications and additions with no hypercomplex code, the complex or hypercomplex algebra being represented by the form of the matrix root of -1, so that the matrix multiplications are equivalent to multiplications in the appropriate algebra. We present examples from the complex, quaternion and biquaternion algebras, and from Clifford algebras Cl1,1 and Cl2,0. The significance of this result is both in the theoretical unification, and also in the scope it affords for insight into the structure of the various transforms, since the formulation is such a simple generalization of the classic complex case. It also shows that hypercomplex discrete Fourier transforms may be computed using standard matrix arithmetic packages without the need for a hypercomplex library, which is of importance in providing a reference implementation for verifying implementations based on hypercomplex code.Comment: The paper has been revised since the second version to make some of the reasons for the paper clearer, to include reviews of prior hypercomplex transforms, and to clarify some points in the conclusion

A Lossy JPEG2000-based Data Hiding Method for Scalable 3D Terrain Visualization

International audienceThe data needed for 3D terrain visualization consists, essentially, of a texture image and its corresponding digital elevation model (DEM). A blind data hiding method is proposed for the synchronous unification of this disparate data whereby the lossless discrete wavelet transformed (DWTed) DEM is embedded in the tier-1 coded quantized and DWTed Y component of the texture image from the lossy JPEG2000 pipeline. The multiresolution nature of wavelets provides us the scalability that can cater for the diversity of client capacities in terms of computing, memory and network resources in today's network environment. The results have been interesting and for a bitrate as low as $0.012$ bit per pixel (bpp), a satisfactory visualization was realized. We compare the obtained results with those of a previous method that interrupt the lossless JPEG2000 codec immediately after the DWT step and embeds lossless DWTed DEM in the reversibly DWTed Y component of texture. The proposed method proved to be more effective in the sense that for the same bitrate one observed lesser quality loss for respective resolutions

Анализ методов обработки последовательностей видеоизображений в приложении к задаче раннего обнаружения пожаров

THE ANALYSIS OF VISION-BASED METHODS FOR EARLY FIRE DETECTION / N. BROVKO, R. BOGUSHРаннее и надежное обнаружение очагов пожаров на открытых пространствах, в зданиях, на территориях промышленных предприятий – важная составляющая любой системы пожарной безопасности. К перспективным направлениям повышения эффективности работы таких систем относят применение видеодетекторов пожаров. В данной работе рассмотрены общие принципы построения алгоритмов автоматического обнаружения на видеопоследовательностях пламени и дыма как основных факторов пожаров. Представлен сравнительный анализ применяемых подходов для цветовой сегментации пламени и дыма, обнаружения движущихся областей, анализа пространственных изменений яркости и временной изменчивости границы области пламени или дыма, отмечены их достоинства и недостатки. Показаны направления развития алгоритмического обеспечения видеодетекторов

Framework For Efficient Cosimulation And Fast Prototyping on Multi-Components With AAA Methodology: LAR Codec Study Case

pp 1667 - 1671Real-time signal and image applications have significant time constraints involving the use of several powerful calculation units. Programmable multi-component architectures have proven to be a suitable solution combining flexibility and computation power. This paper presents a methodology for the fast design of signal and image processing applications. In a unified framework, application modeling, cosimulation and fast implementation onto parallel heterogeneous architectures are enabled and help to reduce time-to-market. Moreover, automatic code generation provides a high abstraction level for users. Finally, the worthwhile nature of Matlab/C language cosimulation is illustrated on a still image codec named LAR

Reduced Complexity Maximum Likelihood Detector for DFT-s-SEFDM Systems

In this paper, we report on the design of a Complexity-Reduced Maximum Likelihood (CRML) detector for DFT-spread Spectrally Efficient Frequency Division Multiplexing (DFT-s-SEFDM) systems. DFT-s-SEFDM systems are similar to DFT-spread Orthogonal Frequency Division Multiplexing (DFT-s-OFDM) systems, yet offer improved spectral efficiency. Simulation results demonstrate that the CRML detector can achieve the same bit error rate (BER) performance as the ML detector in DFT-s-SEFDM systems at reduced computational complexity. Specifically, compared to a conventional ML detector, it is shown that CRML can decrease the search region by up to 2^{M} times where M denotes the constellation cardinality. Depending on parameter configuration, CRML can offer up to two orders of magnitude improvement in execution runtime performance. CRML is best-suited to applications with small system sizes, for example, in narrowband Internet of Things (NB-IoT) networks