Algorithmic and architectural design for real-time and power-efficient Retinex image/video processing

This paper presents novel algorithmic and architectural solutions for real-time and power-efficient enhancement of images and video sequences. A programmable class of Retinex-like filters, based on the separation of the illumination and reflectance components, is proposed. The dynamic range of the input image is controlled by applying a suitable non-linear function to the illumination, while the details are enhanced by processing the reflectance. An innovative spatially recursive rational filter is used to estimate the illumination. Moreover, to improve the visual quality results of two-branch Retinex operators when applied to videos, a novel three-branch technique is proposed which exploits both spatial and temporal filtering. Real-time implementation is obtained by designing an Application Specific Instruction-set Processor (ASIP). Optimizations are addressed at algorithmic and architectural levels. The former involves arithmetic accuracy definition and linearization of non-linear operators; the latter includes customized instruction set, dedicated memory structure, adapted pipeline, bypasses, custom address generator, and special looping structures. The ASIP is synthesized in standard-cells CMOS technology and its performances are compared to known Digital signal processor (DSP) implementations of real-time Retinex filters. As a result of the comparison, the proposed algorithmic/architectural design outperforms state-of-art Retinex-like operators achieving the best trade-off between power consumption, flexibility, and visual quality.

Human cytidine deaminase: a three-dimensional homology model of a tetrameric metallo-enzyme inferred from the crystal structure of a distantly related dimeric homologue

Cytidine deaminase (CDA) is a cytosolic metalloprotein whose functional unit can be either a homotetramer (T-CDA) or a homodimer (D-CDA), depending on the species. In 1994, the first crystal structure of the dimeric Escherichia coli CDA has been published. However, a crystal structure of a tetrameric CDA was not determined until 2002. Prior to the disclosure of the experimentally elucidated structure of a tetrameric CDA, we derived a homology model of the human T-CDA employing the crystal structure of the dimeric E. coli CDA as a template. The comparison of our theoretical model with the crystal structure of the human T-CDA, subsequently published in 2004, validates our prediction: not only of the structural features of the monomer and the details of the binding site, but also the multimeric arrangement of the subunits were determined with high accuracy in our model. By means of a phylogenetic analysis conducted on CDAs from various organisms, we demonstrate that the E. coli CDA is one of the furthest known homologues of the human enzyme. Nonetheless, despite the evolutionary distance and, more importantly, the different multimeric arrangement of their functional units, the E. coli CDA proved to have all the necessary information to accurately infer the structure of its human homologue.     

Incorporating biologically based models into assessments of risk from chemical contaminants

The general approach to assessment of risk from chemical contaminants in drinking water involves three steps: hazard identification, exposure assessment, and dose-response assessment. Traditionally, the risks to humans associated with different levels of a chemical have been derived from the toxic responses observed in animals. It is becoming increasingly clear, however, that further information is needed if risks to humans are to be assessed accurately. Biologically based models help clarify the dose-response relationship and reduce uncertainty.     

Minimize the Maximum Duty in Multi-interface Networks

We consider devices equipped with multiple wired or wireless interfaces. By switching of various interfaces, each device might establish several connections. A connection is established when the devices at its endpoints share at least one active interface. Each interface is assumed to require an activation cost. In this paper, we consider two basic networking problems in the field of multi-interface networks. The first one, known as the Coverage problem, requires to establish the connections defined by a network. The second one, known as Connectivity problem, requires to guarantee a connecting path between any pair of nodes of a network. Both are subject to the constraint of keeping as low as possible the maximum cost set of active interfaces at each single node. We study the problems of minimizing the maximum cost set of active interfaces among the nodes of the network in order to cover all the edges in the first case, or to ensure connectivity in the second case. We prove that the Coverage problem is NP-hard for any fixed Δ≥5 and k≥16, with Δ being the maximum degree, and k being the number of different interfaces among the network. We also show that, unless P=NP, the problem cannot be approximated within a factor of ηln?Δ, for a certain constant η. We then provide a general approximation algorithm which guarantees a factor of O((1+b)ln?Δ), with b being a parameter depending on the topology of the input graph. Interestingly, b can be bounded by a constant for many graph classes. Other approximation and exact algorithms for special cases are presented. Concerning the Connectivity problem, we prove that it is NP-hard for any fixed Δ≥3 and k≥10. Also for this problem, the inapproximability result holds, that is, unless P=NP, the problem cannot be approximated within a factor of ηln?Δ, for a certain constant η. We then provide approximation and exact algorithms for the general problem and for special cases, respectively.     

A new separation result for a class of quadratic-like systems with application to Euler-Lagrange models

A separation result for some kind of global stabilization via output feedback of a class of nonlinear systems, under the form of some stabilizability by state feedback on the one hand, and some unboundedness observability on the other hand is presented. They allow to design, for any domain of output initial condition, some dynamic output feedback controller achieving global stability. It is also highlighted how disturbance attenuation can further be achieved on the same basis. As an example, the proposed conditions are shown to be satisfied by the class of so-called Euler-Lagrange systems, for which a tracking output feedback control law is thus proposed.     

Formal methods integration for the specification of dependable distributed systems

This paper describes a real-world case study in the specification and analysis of dependable distributed systems. The case study is an automated transport system with safety requirements. In order to manage the complexity of the problem of specifying the dynamic behavior of the whole system, a compositional approach is used, based on the integration of the trace logic of the Communicating Sequential Processes (CSP) theory, and stochastic Petri nets (SPNs). It is argued that the integration of different formal methods is a useful approach in the definition of practical engineering methodologies for the specification, design and analysis of complex dependable distributed systems.     

An efficient technique for implementing an image-compression neural algorithm on concurrent multiprocessor architectures

The paper describes a parallel implementation of a neural algorithm performing vector quantization for very low bit-rate video compression on toroidal-mesh multiprocessor systems. The neural model considered is a plastic version of the Neural Gas algorithm, whose features are suitable for implementations on toroidal mesh topologies. The architecture adopted, and the data-allocation strategy, enhance the method's scaling properties and remarkable efficiency. The parallel approach is supported by a theoretical analysis of the efficiency of the overall structure. Experimental results on a significant testbed and the fit between predicted and measured values confirm the validity of the parallel approach.     

Merging Results for Distributed Content Based Image Retrieval

Searching information through the Internet often requires users to separately contact several digital libraries, use each library interface to author the query, analyze retrieval results and merge them with results returned by other libraries. Such a solution could be simplified by using a centralized server that acts as a gateway between the user and several distributed repositories: The centralized server receives the user query, forwards the user query to federated repositories—possibly translating the query in the specific format required by each repository—and fuses retrieved documents for presentation to the user. To accomplish these tasks efficiently, the centralized server should perform some major operations such as: resource selection, query transformation and data fusion. In this paper we report on some aspects of MIND, a system for managing distributed, heterogeneous multimedia libraries (MIND, 2001, http://www.mind-project.org). In particular, this paper focusses on the issue of fusing results returned by different image repositories. The proposed approach is based on normalization of matching scores assigned to retrieved images by individual libraries. Experimental results on a prototype system show the potential of the proposed approach with respect to traditional solutions.     

Distribution of nitric oxide synthase immunoreactivity in the mouse brain

Nitric oxide (NO) is a gaseous intercellular messenger with a wide range of neural functions. NO is synthesized by activation of different isoforms of nitric oxide synthases (NOS). At present NOS immunoreactivity has been described in mouse brain in restricted and definite areas and no detailed mapping studies have yet been reported for NOS immunoreactivity. We have studied the distribution of neuronal NOS-containing neurons in the brain of three months male mice, using a specific commercial polyclonal antibody against the neuronal isoform of nitric oxide synthase (nNOS). Neuronal cell bodies exhibiting nNOS immunoreactivity were found in several distinct nuclei throughout the brain. The neurons that were positively stained exhibited different intensities of reaction. In some brain areas (i.e., cortex, striatum, tegmental nuclei) neurons were intensely stained in a Golgi-like fashion. In other regions, immunoreactive cells are moderately stained (i.e., magnocellular nucleus of the posterior commissure, amygdaloid nucleus, interpeduncular nucleus, lateral periaqueductal gray) or weakly stained (i.e., vascular organ of the lamina terminalis, hippocampus, inferior colliculus, reticular nucleus). In the mouse, the NO-producing system appears well developed and widely diffused. In particular, nNOS immunoreactive neurons seem chiefly present in several sensory pathways like all the nuclei of the olfactory system, as well as in many regions of the lymbic system. These data suggest a widespread role for the NO system in the mouse nervous system.