A taxonomic classification of dedicated microprocessor applications

The principles and uses of taxonomic classification for dedicated microprocessor applications are discussed and a classification is proposed. A population of devices, produced by the author, is mapped into the classification schema and typical characteristics of devices used in particular applications are estimated. It is suggested that the taxonomically derived characters may be of value for expert system design programs and in producing more efficient designs for dedicated microprocessor applications.     

A RISC processor for embedded applications within an ASIC

The VL86C010 processor, which is well suited to RISC applications because of its small die size, low power dissipation, and low pin count, is presented. This RISC processor family was designed for maximum system performance at minimum cost, rather than maximum CPU performance at any cost. The components of the system CPU, memory controller, IO controller, and video controller were partitioned to take advantage of less-expensive plastic IC packages and, more importantly, less-expensive dynamic RAM devices (DRAMs) by using their page mode of operation. These components are described, and the processor performance is examined     

A security approach for off-chip memory in embedded microprocessor systems

This paper describes a complete off-chip memory security solution for embedded systems. Our security core is based on a one-time pad (OTP) encryption circuit and a CRC-based integrity checking module. These modules safeguard external memory used by embedded processors against a series of well-known attacks, including replay attacks, spoofing attacks and relocation attacks. Our implementation limits on-chip memory space overhead to less than 33% versus memory used by a standard microprocessor and reduces memory latency achieved by previous approaches by at least half. The performance loss for software execution with our solution is only 10% compared with a non-protected implementation. An FPGA prototype of our security core has been completed to validate our findings.     

Optimizing memory bandwidth exploitation for OpenVX applications on embedded many-core accelerators

In recent years, image processing has been a key application area for mobile and embedded computing platforms. In this context, many-core accelerators are a viable solution to efficiently execute highly parallel kernels. However, architectural constraints impose hard limits on the main memory bandwidth, and push for software techniques which optimize the memory usage of complex multi-kernel applications. In this work, we propose a set of techniques, mainly based on graph analysis and image tiling, targeted to accelerate the execution of image processing applications expressed as standard OpenVX graphs on cluster-based many-core accelerators. We have developed a run-time framework which implements these techniques using a front-end compliant to the OpenVX standard, and based on an OpenCL extension that enables more explicit control and efficient reuse of on-chip memory and greatly reduces the recourse to off-chip memory for storing intermediate results. Experiments performed on the STHORM many-core accelerator demonstrate that our approach leads to massive reduction of time and bandwidth, even when the main memory bandwidth for the accelerator is severely constrained.     

Modular hardware of reduced performance for dedicated microprocessor applications: examples and justification

There is a domain in which general-purpose modular hardware is the most economic approach for implementing microprocessor-based devices. Existing modular hardware, however, tends to be directed towards high performance rather than economy. The needs of the domain are inferred by analysing 32 past applications. A family of reduced-performance modular hardware, Greenbus, is discussed. The reduced-performance design approach is found to be justifiable, economic and well suited for a wide range of dedicated microprocessor applications.     

A renormalization group approach to image processing problems

A method for studying problems in digital image processing, based on a combination of renormalization group ideas, the Markov random-field modeling of images, and metropolis-type Monte Carlo algorithms, is presented. The method is efficiently implementable on parallel architectures, and provides a unifying procedure for performing a hierarchical, multiscale, coarse-to-fine analysis of image-processing tasks such as restoration, texture analysis, coding, motion analysis, etc. The method is formulated and applied to the restoration of degraded images. The restoration algorithm is a global-optimization algorithm applicable to other optimization problems. It generates iteratively a multilevel cascode of restored images corresponding to different levels of resolution, or scale. In the lower levels of the cascade appear the large-scale features of the image, and in the higher levels, the microscopic features of the image     

A state variable approach to digital image processing

Digital filtering of images is considered. A recursive filter design for two-dimensional separable filters is discussed which is based on state variable methods. Advantages of this design are guaranteed stability, and shorter word length than filters designed by bilinear mapping techniques, greater computational efficiency and easier design as compared with nonrecursive filters. Results are shown for filtering high frequency additive noise from a low spatial frequency image and for filtering a low frequency multiplicative noise from a high spatial frequency image.     

A new approach to morphological color image processing

This paper presents a new approach to the generalization of the concepts of grayscale morphology to color images. A new vector ordering scheme is proposed, infimum and supremum operators are defined, and the fundamental vector morphological operations are extracted. The basic properties of the presented vector morphology are described and its similarities to grayscale morphological operators are pointed out. The main advantages of the proposed methodology are that is vector preserving and provides improved results in many morphological applications. Furthermore, experimental results demonstrate the applicability of the proposed technique in a number of image processing and analysis problems, such as noise removal, edge detection and skeleton extraction.     

A unified link-layer fault-tolerant architecture for network-based many-core embedded systems

Reliability is an important design concern for modern many-core embedded systems. Specifically, on-chip interconnecting systems are vulnerable to permanent channel faults and transient data transmission faults which may significantly impact the overall system performance. In this work, a Unified Link-layer Fault-tolerant NoC (ULF-NoC) architecture is proposed. ULF-NoC is developed for NoC equipped with bidirectional channels and features wormhole switching (instead of store-and-forward switching) and packet-based retransmission. An intelligent buffer controller is developed that does not require separate, dedicated buffer spaces to support packet retransmissions. Extensive simulations using both synthetic and real world data traffics demonstrated marked performance of the proposed ULF-NoC solution.     

A novel method for parallel image processing applications

It is the aim of this paper to introduce a novel method for the calculation of 2-D convolution/correlation for image processing application. The technique combines a recently developed 2-D transform based on the Mersenne numbers with the 2-D Fermat number transform, using the 2-D mixed radix conversion. The resulting combination uses fast two dimensional residue transforms which can be implemented in parallel for high speed and high throughput rate. The technique is suitable for parallel calculation of 2-D convolution/correlation for digital image processing applications purposes.     

An image processing approach to computer graphics

Computer graphics was conceived as, and remains for the most part, a line-drawing phenomenon. The cautious management of display lists or of in-line vector generators has captured most of the attention of researchers in computer graphics. Cathode ray tubes with randomly positionable beams have served as the primary medium for this research and development.The underlying position of this paper is that the future of computer graphics does not lie in ‘vectored’ displays but in raster scan television, conceivably as we know it in our homes. This posture is motivated by arguments of cost and compatibility, but the most salient motivation comes in view of the ubiquitous nature of raster scan display technologies.This paper explains a way to implement an image processing approach to computer graphics, one that is conceptually straightforward and, in terms of hardware, fairly easy to design. A device is being built that encompases as much as is known about raster scan, multi-bit per point displays. The work described is conducted, principally, to produce a multi-bit per point graphics output device that dynamically shares its image storage with the memory space of an expanded mini-computer.     

嵌入式浏览器图像处理技术研究

分析了嵌入式浏览器图像处理的关键问题,设计并实现了嵌入式浏览器Jlbrowser的图像处理技术。该技术对图像采用多线程传输、分块解码、缓存和重排,提高了网页的显示速度。     

基于形态学和小波的遥感图像边缘检测

针对遥感图像噪声含量大、边缘细节丰富等特点,提出了一种基于形态学和小波分析相结合的遥感图像边缘检测方法,即利用小波变换将遥感图像分解为低频和高频两部分分别进行处理,低频采用形态学锐化算法改善低频边缘清晰度后构造全方位多结构元素进行形态学边缘检测,高频引入小波阈值去噪算法进行预处理后利用小波模极大值进行边缘检测,最后进行边缘图像融合.实验结果表明:该方法在有效抑制噪声的同时,实现了边缘的精确定位,细节提取效果好.     

The TMS34010: an embedded microprocessor

The authors discuss the TMS34010, a high-performance 32-bit microprocessor with special instructions and hardware for handling the bit-field data and address manipulations often associated with computer graphics. They give a history of embedded microprocessors and examine the wide range of processors and applications covered by that term. They provide an overview of the internal architecture of the TMS34010 and discuss the choice of feature set in its design. Although it is aimed at graphics systems, the processor's large address reach, bit-field processing, and DRAM (dynamic random-access memory) interface make it suitable for many other embedded processing applications.<>     

嵌入式DSP技术在夜视图像处理技术中的应用

针对夜视图像暗处太暗,亮处太亮以及图像质量变坏的问题,利用嵌入式DSP系统进行图像实时处理,通过图像算法的研究和实验,利用图像分段灰度变换、边缘检测、图像帧积累等技术能够改善夜视图像的质量。     

Specific applications of image processing to surface flaw detection

An approach to detect surface flaws automatically through digital image processing techniques is investigated in this work. In addition, a novel pre-processing transducer applicable to this area is presented.The digitized image of the surface of a part to be inspected is obtained by means of a vidicon camera. The image is then properly segmented to separate the information-bearing objects from the background by means of a thresholding scheme. An analysis of the resulting binary image is then made by following the borders present.Objects on interest in the image can be located by means of template matching. The use of a hardware Number Theoretic Transform (NTT) convulutional filter is shown to provide processing times commensurate with industrial requirements.Results arer shown for 3 practical cases in which the system was used to detect surface flaws.To assist in the measurement of surface flaws a transducer is introduced which converts true surface-depth information into a gray level image for processing by the system.     

A novel image decomposition approach and its applications

The current state-of-the-art edge-preserving decomposition techniques may not be able to fully separate textures while preserving edges. This may generate artifacts in some applications, e.g., edge detection, texture transfer, etc. To solve this problem, a novel image decomposition approach based on explicit texture separation from large scale components of an image is presented. We first apply a Gaussian structure-texture decomposition, to separate the majority of textures out of the input image. However, residual textures are still visible around the strong edges. To remove these residuals, an asymmetric sampling operator is proposed and followed by a joint bilateral correction to remove an excessive blur effect. We demonstrate that our approach is well suited for the tasks such as texture transfer, edge detection, non-photorealistic rendering, and tone mapping. The results show our approach outperforms existing state-of-the-art image decomposition approaches.     

Tensor scale: A local morphometric parameter with applications to computer vision and image processing

Scale is a widely used notion in image analysis that evolved in the form of scale-space theory whose key idea is to represent and analyze an image at various resolutions. Recently, the notion of localized scale—a space-variant resolution scheme—has drawn significant research interest. Previously, we reported local morphometric scale using a spherical model. A major limitation of the spherical model is that it ignores structure orientation and anisotropy, and therefore fails to be optimal in many imaging applications including biomedical ones where structures are inherently anisotropic and have mixed orientations. Here, we introduce a new concept called “tensor scale”—a local morphometric parameter yielding a unified representation of structure size, orientation, and anisotropy. Also, a few applications of tensor scale in computer vision and image analysis, especially, in image filtering are illustrated. At any image point, its tensor scale is the parametric representation of the largest ellipse (in 2D) or ellipsoid (in 3D) centered at that point and contained in the same homogeneous region. An algorithmic framework to compute tensor scale at any image point is proposed and results of its application on several real images are presented. Also, performance of the tensor scale computation method under image rotation, varying pixel size, and background inhomogeneity is studied. Results of a quantitative analysis evaluating performance of the method on 2D brain phantom images at various levels of noise and blur, and a fixed background inhomogeneity are presented. Agreement between tensor scale images computed on matching image slices from two 3D magnetic resonance data acquired simultaneously using different protocols are demonstrated. Finally, the application of tensor scale in anisotropic diffusive image filtering is presented that encourages smoothing inside a homogeneous region and also along edges and elongated structures while discourages blurring across them. Both qualitative and quantitative results of application of the new filtering method have been presented and compared with the results obtained by spherical scale-based and standard diffusive filtering methods.     

A fuzzy mathematical morphology based on discrete t-norms: fundamentals and applications to image processing

In this paper, a new approach to fuzzy mathematical morphology based on discrete t-norms is studied. The discrete t-norms that have to be used in order to preserve the most usual algebraical and morphological properties, such as monotonicity, idempotence, scaling invariance, among others, are fully determined. In addition, the properties related to B-open and B-closed objects and the generalized idempotence are also studied. In fact, all properties satisfied by the approach based on continuous nilpotent t-norms hold in the discrete case. This is quite important since in practice we only work with discrete objects. In addition, it is proved that more discrete t-norms satisfying all the properties are available in this approach than in the continuous case, which reduces to the ?ukasiewicz t-norm. This morphology based on discrete t-norms can be considered embedded in more general frameworks, such as L-fuzzy sets or quantale modules, but all these frameworks have been studied only from a theoretical point of view. Our main contribution is the practical application of this discrete approach to image processing. Experimental results on edge detection, noise removal and top-hat transformations for some discrete t-norms and their comparison with the corresponding ones obtained by the umbra approach and the continuous ?ukasiewicz t-norm are included showing that this theory can be suitable to be used in a wide range of applications on image processing. In particular, a new edge detector based on the morphological gradient, non-maxima suppression and a hysteresis method is presented.     

嵌入式图像处理系统的设计与实现

针对传统图像处理技术依赖于大批量电子设备的问题,提出了嵌入式技术和图像处理技术相结合的嵌入式图像处理系统的概念.以嵌入式微处理器S3C44BOX为系统硬件核心,以ucos为操作系统平台,以模块化为软件设计理念,设计与实现了完备的嵌入式图像处理系统.测试结果表明,系统运行良好,在嵌入式系统较少的软硬件资源上实现了实时性较强,显示清晰的数字图像处理的结果.