Combined wavelet domain and motion compensated filtering compliant with video codecs

In this paper, we introduce the idea of using motion estimation resources from a video codec for video denoising. This is not straightforward because the motion estimators aimed for video compression and coding, tolerate errors in the estimated motion field and hence are not directly applicable to video denoising. To solve this problem, we propose a novel motion field filtering step that refines the accuracy of the motion estimates to a degree that is required for denoising. We illustrate the use of the proposed motion estimation method within a wavelet-based video denoising scheme. The resulting video denoising method is of low-complexity and receives comparable results with respect to the latest video denoising methods

Filter tuning system using fuzzy logic

The authors describe an expert system approach for tuning filters using fuzzy logic. The proposed system adjusts the filter components in order to meet the given window specifications. The system is described and experimental results are presented for a lowpass filter implemented with OTA

Embedded video stabilization system on field programmable gate array for unmanned aerial vehicle

Unmanned Aerial Vehicles (UAVs) equipped with lightweight and low-cost cameras have grown in popularity and enable new applications of UAV technology. However, the video retrieved from small size UAVs is normally in low-quality due to high frequency jitter. This thesis presents the development of video stabilization algorithm implemented on Field Programmable Gate Array (FPGA). The video stabilization algorithm consists of three main processes, which are motion estimation, motion stabilization and motion compensation to minimize the jitter. Motion estimation involves block matching and Random Sample Consensus (RANSAC) to estimate the affine matrix that defines the motion perspective between two consecutive frames. Then, parameter extraction, motion smoothing and motion vector correction, which are parts of the motion stabilization, are tasked in removing unwanted camera movement. Finally, motion compensation stabilizes two consecutive frames based on filtered motion vectors. In order to facilitate the ground station mobility, this algorithm needs to be processed onboard the UAV in real-time. The nature of parallelization of video stabilization processing is suitable to be utilized by using FPGA in order to achieve real-time capability. The implementation of this system is on Altera DE2-115 FPGA board. Full hardware dedicated cores without Nios II processor are designed in stream-oriented architecture to accelerate the computation. Furthermore, a parallelized architecture consisting of block matching and highly parameterizable RANSAC processor modules show that the proposed system is able to achieve up to 30 frames per second processing and a good stabilization improvement up to 1.78 Interframe Transformation Fidelity value. Hence, it is concluded that the proposed system is suitable for real-time video stabilization for UAV application

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

FPGA design methodology for industrial control systems—a review

This paper reviews the state of the art of fieldprogrammable gate array (FPGA) design methodologies with a focus on industrial control system applications. This paper starts with an overview of FPGA technology development, followed by a presentation of design methodologies, development tools and relevant CAD environments, including the use of portable hardware description languages and system level programming/design tools. They enable a holistic functional approach with the major advantage of setting up a unique modeling and evaluation environment for complete industrial electronics systems. Three main design rules are then presented. These are algorithm refinement, modularity, and systematic search for the best compromise between the control performance and the architectural constraints. An overview of contributions and limits of FPGAs is also given, followed by a short survey of FPGA-based intelligent controllers for modern industrial systems. Finally, two complete and timely case studies are presented to illustrate the benefits of an FPGA implementation when using the proposed system modeling and design methodology. These consist of the direct torque control for induction motor drives and the control of a diesel-driven synchronous stand-alone generator with the help of fuzzy logic

VLSI Design

This book provides some recent advances in design nanometer VLSI chips. The selected topics try to present some open problems and challenges with important topics ranging from design tools, new post-silicon devices, GPU-based parallel computing, emerging 3D integration, and antenna design. The book consists of two parts, with chapters such as: VLSI design for multi-sensor smart systems on a chip, Three-dimensional integrated circuits design for thousand-core processors, Parallel symbolic analysis of large analog circuits on GPU platforms, Algorithms for CAD tools VLSI design, A multilevel memetic algorithm for large SAT-encoded problems, etc