A reduced-reference perceptual image and video quality metric based on edge preservation

In image and video compression and transmission, it is important to rely on an objective image/video quality metric which accurately represents the subjective quality of processed images and video sequences. In some scenarios, it is also important to evaluate the quality of the received video sequence with minimal reference to the transmitted one. For instance, for quality improvement of video transmission through closed-loop optimisation, the video quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original image/video sequence-prior to compression and transmission-is not usually available at the receiver side, and it is important to rely at the receiver side on an objective video quality metric that does not need reference or needs minimal reference to the original video sequence. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art RR metric. © 2012 Martini et al

A Fast Kirsch Edge Detection Algorithm Based on GPU

传统的kIrSCH边缘检测算法的优化和实现都是针对常用处理器提出的。根据kIrSCH算法的可并行计算的特点,本文提出了一种基于图形处理器gPu的快速kIrSCH算法。快速算法根据gPu的并行结构和硬件特点,采用了纹理存储技术、多点访问技术和对称计算技术三种加速技术,优化了数据存储结构,提高了数据访问效率,降低了算法复杂度。实验表明,采用基于gPu的算法可将对图像的处理速度提高到传统kIrSCH边缘检测算法的10倍以上。The traditional Kirsch edge detection algorithms for optimization and implementation which were designed for common processor.According to parallel computing capability of Kirsch algorithm,a fast Kirsch edge detection algorithm is presented based on GPU.On the basis of the parallel architecture and hardware characteristic of GPU,the fast algorithm introduces three methods to improve the implementation performance: Texture Storage technology optimizes the data storage structure,multiple point access technology improves the data access efficiency,and symmetry computation technology reduces the computation complex.The experiment expressed that we could get a over ten times speed effect by this method than traditional Kirsch algorithm.漳州职业技术学院科研计划资助项目;项目编号:ZZY110

OCLoptimizer: an iterative optimization tool for OpenCL

Abstract Nowadays, computers include several computational devices with parallel capacities, such as multicore processors and Graphic Processing Units (GPUs). OpenCL enables the programming of all these kinds of devices. An OpenCL program consists of a host code which discovers the computational devices available in the host system and it queues up commands to the devices, and the kernel code which defines the core of the parallel computation executed in the devices. This work addresses two of the most important problems faced by an OpenCL programmer: (1) hosts codes are quite verbose but they can be automatically generated if some parameters are known; (2) OpenCL codes that are hand-optimized for a given device do not get necessarily a good performance in a different one. This paper presents a source-to-source iterative optimization tool, called OCLoptimizer, that aims to generate host codes automatically and to optimize OpenCL kernels taking as inputs an annotated version of the original kernel and a configuration file. Iterative optimization is a well-known technique which allows to optimize a given code by exploring different configuration parameters in a systematic manner. For example, we can apply tiling on one loop and the iterative optimizer would select the optimal tile size by exploring the space of possible tile sizes. The experimental results show that the tool can automatically optimize a set of OpenCL kernels for multicore processors

Image-Based Fracture Mechanics with Digital Image Correlation and Digital Volume Correlation

Analysis that requires human judgement can add bias which may, as a result, increase uncertainty. Accurate detection of a crack and segmentation of the crack geometry is beneficial to any fracture experiment. Studies of crack behaviour, such as the effect of closure, residual stress in fatigue or elastic-plastic fracture mechanics, require data on crack opening displacement. Furthermore, the crack path can give critical information of how the crack interacts with the microstructure and stress fields. Digital Image Correlation (DIC) and Digital Volume Correlation (DVC) have been widely accepted and routinely used to measure full-field displacements in many areas of solid mechanics, including fracture mechanics. However, current practise for the extraction of crack parameters from displacement fields usually requires manual methods and are quite onerous, particularly for large amounts of data. This thesis introduces the novel application of Phase Congruency-based Crack Detection (PC-CD) to automatically detect and characterise cracks from displacement fields. Phase congruency is a powerful mathematical tool that highlights a discontinuity more efficiently than gradient based methods. Phase congruency’s invariance to the magnitude of the discontinuity and its state-of-the-art de-noising method, make it ideal for the application to crack tip displacement fields. PC-CD’s accuracy is quantified and benchmarked using both theoretical and virtual displacement fields. The accuracy of PC-CD is evaluated and compared with conventional, manual computation methods such as Heaviside function fitting and gradient based methods. It is demonstrated how PC-CD can be coupled with a new method that is based on the conjoint use of displacement fields and finite element analysis to extract the strain energy release rate of cracks automatically. The PC-CD method is extended to volume displacement fields (VPC-CD) and semi-autonomously extracts crack surface, crack front and opening displacement through the thickness. As a proof of concept, PC-CD and VPC-CD are applied to a range of fracture experiments varying in material and fracture behaviour: two ductile and one quasi-brittle for surface displacement measurements; and two quasi-brittle and one ductile for volume measurements. Using the novel PC-CD and VPC-CD analyses, the crack geometry is obtained fully automatically and without any user judgement or intervention. The geometrical parameters extracted by PC-CD and VPC-CD are validated experimentally through other tools such as: optical microscope measurements, high resolution fractography and visual inspection

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity