Efficient reconfigurable architectures for 3D medical image compression

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Recently, the more widespread use of three-dimensional (3-D) imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US) have generated a massive amount of volumetric data. These have provided an impetus to the development of other applications, in particular telemedicine and teleradiology. In these fields, medical image compression is important since both efficient storage and transmission of data through high-bandwidth digital communication lines are of crucial importance. Despite their advantages, most 3-D medical imaging algorithms are computationally intensive with matrix transformation as the most fundamental operation involved in the transform-based methods. Therefore, there is a real need for high-performance systems, whilst keeping architectures exible to allow for quick upgradeability with real-time applications. Moreover, in order to obtain efficient solutions for large medical volumes data, an efficient implementation of these operations is of significant importance. Reconfigurable hardware, in the form of field programmable gate arrays (FPGAs) has been proposed as viable system building block in the construction of high-performance systems at an economical price. Consequently, FPGAs seem an ideal candidate to harness and exploit their inherent advantages such as massive parallelism capabilities, multimillion gate counts, and special low-power packages. The key achievements of the work presented in this thesis are summarised as follows. Two architectures for 3-D Haar wavelet transform (HWT) have been proposed based on transpose-based computation and partial reconfiguration suitable for 3-D medical imaging applications. These applications require continuous hardware servicing, and as a result dynamic partial reconfiguration (DPR) has been introduced. Comparative study for both non-partial and partial reconfiguration implementation has shown that DPR offers many advantages and leads to a compelling solution for implementing computationally intensive applications such as 3-D medical image compression. Using DPR, several large systems are mapped to small hardware resources, and the area, power consumption as well as maximum frequency are optimised and improved. Moreover, an FPGA-based architecture of the finite Radon transform (FRAT)with three design strategies has been proposed: direct implementation of pseudo-code with a sequential or pipelined description, and block random access memory (BRAM)- based method. An analysis with various medical imaging modalities has been carried out. Results obtained for image de-noising implementation using FRAT exhibits promising results in reducing Gaussian white noise in medical images. In terms of hardware implementation, promising trade-offs on maximum frequency, throughput and area are also achieved. Furthermore, a novel hardware implementation of 3-D medical image compression system with context-based adaptive variable length coding (CAVLC) has been proposed. An evaluation of the 3-D integer transform (IT) and the discrete wavelet transform (DWT) with lifting scheme (LS) for transform blocks reveal that 3-D IT demonstrates better computational complexity than the 3-D DWT, whilst the 3-D DWT with LS exhibits a lossless compression that is significantly useful for medical image compression. Additionally, an architecture of CAVLC that is capable of compressing high-definition (HD) images in real-time without any buffer between the quantiser and the entropy coder is proposed. Through a judicious parallelisation, promising results have been obtained with limited resources. In summary, this research is tackling the issues of massive 3-D medical volumes data that requires compression as well as hardware implementation to accelerate the slowest operations in the system. Results obtained also reveal a significant achievement in terms of the architecture efficiency and applications performance.Ministry of Higher Education Malaysia (MOHE), Universiti Tun Hussein Onn Malaysia (UTHM) and the British Counci

Energy efficient enabling technologies for semantic video processing on mobile devices

Semantic object-based processing will play an increasingly important role in future multimedia systems due to the ubiquity of digital multimedia capture/playback technologies and increasing storage capacity. Although the object based paradigm has many undeniable benefits, numerous technical challenges remain before the applications becomes pervasive, particularly on computational constrained mobile devices. A fundamental issue is the ill-posed problem of semantic object segmentation. Furthermore, on battery powered mobile computing devices, the additional algorithmic complexity of semantic object based processing compared to conventional video processing is highly undesirable both from a real-time operation and battery life perspective. This thesis attempts to tackle these issues by firstly constraining the solution space and focusing on the human face as a primary semantic concept of use to users of mobile devices. A novel face detection algorithm is proposed, which from the outset was designed to be amenable to be offloaded from the host microprocessor to dedicated hardware, thereby providing real-time performance and reducing power consumption. The algorithm uses an Artificial Neural Network (ANN), whose topology and weights are evolved via a genetic algorithm (GA). The computational burden of the ANN evaluation is offloaded to a dedicated hardware accelerator, which is capable of processing any evolved network topology. Efficient arithmetic circuitry, which leverages modified Booth recoding, column compressors and carry save adders, is adopted throughout the design. To tackle the increased computational costs associated with object tracking or object based shape encoding, a novel energy efficient binary motion estimation architecture is proposed. Energy is reduced in the proposed motion estimation architecture by minimising the redundant operations inherent in the binary data. Both architectures are shown to compare favourable with the relevant prior art

Energy efficient hardware acceleration of multimedia processing tools

The world of mobile devices is experiencing an ongoing trend of feature enhancement and generalpurpose multimedia platform convergence. This trend poses many grand challenges, the most pressing being their limited battery life as a consequence of delivering computationally demanding features. The envisaged mobile application features can be considered to be accelerated by a set of underpinning hardware blocks Based on the survey that this thesis presents on modem video compression standards and their associated enabling technologies, it is concluded that tight energy and throughput constraints can still be effectively tackled at algorithmic level in order to design re-usable optimised hardware acceleration cores. To prove these conclusions, the work m this thesis is focused on two of the basic enabling technologies that support mobile video applications, namely the Shape Adaptive Discrete Cosine Transform (SA-DCT) and its inverse, the SA-IDCT. The hardware architectures presented in this work have been designed with energy efficiency in mind. This goal is achieved by employing high level techniques such as redundant computation elimination, parallelism and low switching computation structures. Both architectures compare favourably against the relevant pnor art in the literature. The SA-DCT/IDCT technologies are instances of a more general computation - namely, both are Constant Matrix Multiplication (CMM) operations. Thus, this thesis also proposes an algorithm for the efficient hardware design of any general CMM-based enabling technology. The proposed algorithm leverages the effective solution search capability of genetic programming. A bonus feature of the proposed modelling approach is that it is further amenable to hardware acceleration. Another bonus feature is an early exit mechanism that achieves large search space reductions .Results show an improvement on state of the art algorithms with future potential for even greater savings

A scalable packetised radio astronomy imager

Includes bibliographical referencesModern radio astronomy telescopes the world over require digital back-ends. The complexity of these systems depends on many site-specific factors, including the number of antennas, beams and frequency channels and the bandwidth to be processed. With the increasing popularity for ever larger interferometric arrays, the processing requirements for these back-ends have increased significantly. While the techniques for building these back-ends are well understood, every installation typically still takes many years to develop as the instruments use highly specialised, custom hardware in order to cope with the demanding engineering requirements. Modern technology has enabled reprogrammable FPGA-based processing boards, together with packet-based switching techniques, to perform all the digital signal processing requirements of a modern radio telescope array. The various instruments used by radio telescopes are functionally very different, but the component operations remain remarkably similar and many share core functionalities. Generic processing platforms are thus able to share signal processing libraries and can acquire different personalities to perform different functions simply by reprogramming them and rerouting the data appropriately. Furthermore, Ethernet-based packet-switched networks are highly flexible and scalable, enabling the same instrument design to be scaled to larger installations simply by adding additional processing nodes and larger network switches. The ability of a packetised network to transfer data to arbitrary processing nodes, along with these nodes' reconfigurability, allows for unrestrained partitioning of designs and resource allocation. This thesis describes the design and construction of the first working radio astronomy imaging instrument hosted on Ethernet-interconnected re- programmable FPGA hardware. I attempt to establish an optimal packetised architecture for the most popular instruments with particular attention to the core array functions of correlation and beamforming. Emphasis is placed on requirements for South Africa's MeerKAT array. A demonstration system is constructed and deployed on the KAT-7 array, MeerKAT's prototype. This research promises reduced instrument development time, lower costs, improved reliability and closer collaboration between telescope design teams

Development of Low Power Image Compression Techniques

Digital camera is the main medium for digital photography. The basic operation performed by a simple digital camera is, to convert the light energy to electrical energy, then the energy is converted to digital format and a compression algorithm is used to reduce memory requirement for storing the image. This compression algorithm is frequently called for capturing and storing the images. This leads us to develop an efficient compression algorithm which will give the same result as that of the existing algorithms with low power consumption. As a result the new algorithm implemented camera can be used for capturing more images then the previous one. 1) Discrete Cosine Transform (DCT) based JPEG is an accepted standard for lossy compression of still image. Quantisation is mainly responsible for the amount loss in the image quality in the process of lossy compression. A new Energy Quantisation (EQ) method proposed for speeding up the coding and decoding procedure while preserving image qu..

A graph theoretic approach to transputer network design for computer vision

The work in this thesis is concerned with parallel architectures based on the Inmos transputer-type processors and parallelisation of some computer vision tasks chosen from low to high level. The transputer is a microprocessor with a micro-programmed scheduler and four serial communication links. It directly supports parallel processing since several transputers can be connected through their links to co-operate on solving a problem. Also several processes can be run on the same transputer. A major issue in parallel processing is the communication overhead introduced by parallelising a given task. This overhead is not present in sequential processing and must be curbed if the implementation of a task on a parallel machine is to be successful. The interconnection network underlying the architecture of a parallel computer is therefore of the utmost importance. Computer Vision consists of a hierarchy of tasks ranging from low-level operations dealing with large amounts of relatively simple data to high level operations handling increasingly complex structures. In this work a novel edge detector based on adaptive filtering and an edge detector operating on colour images are presented and implemented on a number of transputers. These parallel implementations together with implementations of vector quantisation, Fourier descriptors for shape discrimination, the Hough transform and the Maximum clique algorithm, offer a notable performance increase when compared with sequential implementations. However, every algorithm required the design of a specific network of transputers to take advantage of the parallelism and data dependencies inherent in each. Consequently, attention is focused on the topology of interconnection networks. In particular, the communication requirements of computer vision algorithms as identified by the various computer vision tasks are analysed. These requirements together with graph theoretical considerations are then used to suggest a topology for large transputer networks. The latter is based on sub-graphs, with proven performance when used to implement interconnection networks, combined to form an architecture with improved performance. This architecture consists of a fixed structure supplemented with a dynamically reconfigured network. After describing this topology, a routing algorithm that conveys messages along shortest paths in the network is given and implemented. And finally, some practical issues in the use of transputers are considered and solutions proposed

Digital signal processing optical receivers for the mitigation of physical layer impairments in dynamic optical networks

IT IS generally believed by the research community that the introduction of complex network functions—such as routing—in the optical domain will allow a better network utilisation, lower cost and footprint, and a more efficiency in energy usage. The new optical components and sub-systems intended for dynamic optical networking introduce new kinds of physical layer impairments in the optical signal, and it is of paramount importance to overcome this problem if dynamic optical networks should become a reality. Thus, the aim of this thesis was to first identify and characterise the physical layer impairments of dynamic optical networks, and then digital signal processing techniques were developed to mitigate them. The initial focus of this work was the design and characterisation of digital optical receivers for dynamic core optical networks. Digital receiver techniques allow for complex algorithms to be implemented in the digital domain, which usually outperform their analogue counterparts in performance and flexibility. An AC-coupled digital receiver for core networks—consisting of a standard PIN photodiode and a digitiser that takes samples at twice the Nyquist rate—was characterised in terms of both bit-error rate and packet-error rate, and it is shown that the packet-error rate can be optimised by appropriately setting the preamble length. Also, a realistic model of a digital receiver that includes the quantisation impairments was developed. Finally, the influence of the network load and the traffic sparsity on the packet-error rate performance of the receiver was investigated. Digital receiver technologies can be equally applied to optical access networks, which share many traits with dynamic core networks. A dual-rate digital receiver, capable of detecting optical packets at 10 and 1.25 Gb/s, was developed and characterised. The receiver dynamic range was extended by means of DC-coupling and non-linear signal clipping, and it is shown that the receiver performance is limited by digitiser noise for low received power and non-linear clipping for high received power