Algorithms for the enhancement of dynamic range and colour constancy of digital images & video

One of the main objectives in digital imaging is to mimic the capabilities of the human eye, and perhaps, go beyond in certain aspects. However, the human visual system is so versatile, complex, and only partially understood that no up-to-date imaging technology has been able to accurately reproduce the capabilities of the it. The extraordinary capabilities of the human eye have become a crucial shortcoming in digital imaging, since digital photography, video recording, and computer vision applications have continued to demand more realistic and accurate imaging reproduction and analytic capabilities. Over decades, researchers have tried to solve the colour constancy problem, as well as extending the dynamic range of digital imaging devices by proposing a number of algorithms and instrumentation approaches. Nevertheless, no unique solution has been identified; this is partially due to the wide range of computer vision applications that require colour constancy and high dynamic range imaging, and the complexity of the human visual system to achieve effective colour constancy and dynamic range capabilities. The aim of the research presented in this thesis is to enhance the overall image quality within an image signal processor of digital cameras by achieving colour constancy and extending dynamic range capabilities. This is achieved by developing a set of advanced image-processing algorithms that are robust to a number of practical challenges and feasible to be implemented within an image signal processor used in consumer electronics imaging devises. The experiments conducted in this research show that the proposed algorithms supersede state-of-the-art methods in the fields of dynamic range and colour constancy. Moreover, this unique set of image processing algorithms show that if they are used within an image signal processor, they enable digital camera devices to mimic the human visual system s dynamic range and colour constancy capabilities; the ultimate goal of any state-of-the-art technique, or commercial imaging device

Automatic Field Monitoring and Detection of Plant Diseases Using IoT

This research presents a GSM-based system for automatic plant disease diagnosis and describes its use in the creation of ACPS. Traditional farming methods were largely ineffective against microbial diseases. In addition, farmers can't keep up with the ever-changing nature of infections, so a reliable disease forecasting system is essential. To circumvent this, we employ a Convolutional Neural Network (CNN) model that has been trained to examine the crop image recorded by a health maintenance system. The solar sensor node is in charge of taking pictures, sensing continuously, and automating smartly. An agricultural robot is sometimes known as an agribot or agbot. An autonomous robot with agricultural applications. It helps the farmer improve crop productivity while decreasing the need for manual labour. In the future, these agricultural robots could replace human labour in a variety of farming tasks, including tilling, planting, and harvesting. These agricultural robots will manage pests and diseases as well as perform tasks like weeding. In order to keep an eye on the crops and streamline the irrigation process, this system is equipped with disease prediction technology for plants and intelligent irrigation controls. The energy required to provide disease prediction and irrigation systems separately is reduced by combining them in this project

TechNews digests: Jan - Nov 2009

TechNews is a technology, news and analysis service aimed at anyone in the education sector keen to stay informed about technology developments, trends and issues. TechNews focuses on emerging technologies and other technology news. TechNews service : digests september 2004 till May 2010 Analysis pieces and News combined publish every 2 to 3 month

Performance analysis and application development of hybrid WiMAX-WiFi IP video surveillance systems

Traditional Closed Circuit Television (CCTV) analogue cameras installed in buildings and other areas of security interest necessitates the use of cable lines. However, analogue systems are limited by distance; and storing analogue data requires huge space or bandwidth. Wired systems are also prone to vandalism, they cannot be installed in a hostile terrain and in heritage sites, where cabling would distort original design. Currently, there is a paradigm shift towards wireless solutions (WiMAX, Wi-Fi, 3G, 4G) to complement and in some cases replace the wired system. A wireless solution of the Fourth-Generation Surveillance System (4GSS) has been proposed in this thesis. It is a hybrid WiMAX-WiFi video surveillance system. The performance analysis of the hybrid WiMAX-WiFi is compared with the conventional WiMAX surveillance models. The video surveillance models and the algorithm that exploit the advantages of both WiMAX and Wi-Fi for scenarios of fixed and mobile wireless cameras have been proposed, simulated and compared with the mathematical/analytical models. The hybrid WiMAX-WiFi video surveillance model has been extended to include a Wireless Mesh configuration on the Wi-Fi part, to improve the scalability and reliability. A performance analysis for hybrid WiMAX-WiFi system with an appropriate Mobility model has been considered for the case of mobile cameras. A security software application for mobile smartphones that sends surveillance images to either local or remote servers has been developed. The developed software has been tested, evaluated and deployed in low bandwidth Wi-Fi wireless network environments. WiMAX is a wireless metropolitan access network technology that provides broadband services to the connected customers. Major modules and units of WiMAX include the Customer Provided Equipment (CPE), the Access Service Network (ASN) which consist one or more Base Stations (BS) and the Connectivity Service Network (CSN). Various interfaces exist between each unit and module. WiMAX is based on the IEEE 802.16 family of standards. Wi-Fi, on the other hand, is a wireless access network operating in the local area network; and it is based on the IEEE 802.11 standards

Towards the development of flexible, reliable, reconfigurable, and high-performance imaging systems

Current FPGAs can implement large systems because of the high density of reconfigurable logic resources in a single chip. FPGAs are comprehensive devices that combine flexibility and high performance in the same platform compared to other platform such as General-Purpose Processors (GPPs) and Application Specific Integrated Circuits (ASICs). The flexibility of modern FPGAs is further enhanced by introducing Dynamic Partial Reconfiguration (DPR) feature, which allows for changing the functionality of part of the system while other parts are functioning. FPGAs became an important platform for digital image processing applications because of the aforementioned features. They can fulfil the need of efficient and flexible platforms that execute imaging tasks efficiently as well as the reliably with low power, high performance and high flexibility. The use of FPGAs as accelerators for image processing outperforms most of the current solutions. Current FPGA solutions can to load part of the imaging application that needs high computational power on dedicated reconfigurable hardware accelerators while other parts are working on the traditional solution to increase the system performance. Moreover, the use of the DPR feature enhances the flexibility of image processing further by swapping accelerators in and out at run-time. The use of fault mitigation techniques in FPGAs enables imaging applications to operate in harsh environments following the fact that FPGAs are sensitive to radiation and extreme conditions. The aim of this thesis is to present a platform for efficient implementations of imaging tasks. The research uses FPGAs as the key component of this platform and uses the concept of DPR to increase the performance, flexibility, to reduce the power dissipation and to expand the cycle of possible imaging applications. In this context, it proposes the use of FPGAs to accelerate the Image Processing Pipeline (IPP) stages, the core part of most imaging devices. The thesis has a number of novel concepts. The first novel concept is the use of FPGA hardware environment and DPR feature to increase the parallelism and achieve high flexibility. The concept also increases the performance and reduces the power consumption and area utilisation. Based on this concept, the following implementations are presented in this thesis: An implementation of Adams Hamilton Demosaicing algorithm for camera colour interpolation, which exploits the FPGA parallelism to outperform other equivalents. In addition, an implementation of Automatic White Balance (AWB), another IPP stage that employs DPR feature to prove the mentioned novelty aspects. Another novel concept in this thesis is presented in chapter 6, which uses DPR feature to develop a novel flexible imaging system that requires less logic and can be implemented in small FPGAs. The system can be employed as a template for any imaging application with no limitation. Moreover, discussed in this thesis is a novel reliable version of the imaging system that adopts novel techniques including scrubbing, Built-In Self Test (BIST), and Triple Modular Redundancy (TMR) to detect and correct errors using the Internal Configuration Access Port (ICAP) primitive. These techniques exploit the datapath-based nature of the implemented imaging system to improve the system's overall reliability. The thesis presents a proposal for integrating the imaging system with the Robust Reliable Reconfigurable Real-Time Heterogeneous Operating System (R4THOS) to get the best out of the system. The proposal shows the suitability of the proposed DPR imaging system to be used as part of the core system of autonomous cars because of its unbounded flexibility. These novel works are presented in a number of publications as shown in section 1.3 later in this thesis

Algorithms for compression of high dynamic range images and video

The recent advances in sensor and display technologies have brought upon the High Dynamic Range (HDR) imaging capability. The modern multiple exposure HDR sensors can achieve the dynamic range of 100-120 dB and LED and OLED display devices have contrast ratios of 10^5:1 to 10^6:1. Despite the above advances in technology the image/video compression algorithms and associated hardware are yet based on Standard Dynamic Range (SDR) technology, i.e. they operate within an effective dynamic range of up to 70 dB for 8 bit gamma corrected images. Further the existing infrastructure for content distribution is also designed for SDR, which creates interoperability problems with true HDR capture and display equipment. The current solutions for the above problem include tone mapping the HDR content to fit SDR. However this approach leads to image quality associated problems, when strong dynamic range compression is applied. Even though some HDR-only solutions have been proposed in literature, they are not interoperable with current SDR infrastructure and are thus typically used in closed systems. Given the above observations a research gap was identified in the need for efficient algorithms for the compression of still images and video, which are capable of storing full dynamic range and colour gamut of HDR images and at the same time backward compatible with existing SDR infrastructure. To improve the usability of SDR content it is vital that any such algorithms should accommodate different tone mapping operators, including those that are spatially non-uniform. In the course of the research presented in this thesis a novel two layer CODEC architecture is introduced for both HDR image and video coding. Further a universal and computationally efficient approximation of the tone mapping operator is developed and presented. It is shown that the use of perceptually uniform colourspaces for internal representation of pixel data enables improved compression efficiency of the algorithms. Further proposed novel approaches to the compression of metadata for the tone mapping operator is shown to improve compression performance for low bitrate video content. Multiple compression algorithms are designed, implemented and compared and quality-complexity trade-offs are identified. Finally practical aspects of implementing the developed algorithms are explored by automating the design space exploration flow and integrating the high level systems design framework with domain specific tools for synthesis and simulation of multiprocessor systems. The directions for further work are also presented

Earth imaging with microsatellites: An investigation, design, implementation and in-orbit demonstration of electronic imaging systems for earth observation on-board low-cost microsatellites.

This research programme has studied the possibilities and difficulties of using 50 kg microsatellites to perform remote imaging of the Earth. The design constraints of these missions are quite different to those encountered in larger, conventional spacecraft. While the main attractions of microsatellites are low cost and fast response times, they present the following key limitations: Payload mass under 5 kg, Continuous payload power under 5 Watts, peak power up to 15 Watts, Narrow communications bandwidths (9.6 / 38.4 kbps), Attitude control to within 5°, No moving mechanics. The most significant factor is the limited attitude stability. Without sub-degree attitude control, conventional scanning imaging systems cannot preserve scene geometry, and are therefore poorly suited to current microsatellite capabilities. The foremost conclusion of this thesis is that electronic cameras, which capture entire scenes in a single operation, must be used to overcome the effects of the satellite's motion. The potential applications of electronic cameras, including microsatellite remote sensing, have erupted with the recent availability of high sensitivity field-array CCD (charge-coupled device) image sensors. The research programme has established suitable techniques and architectures necessary for CCD sensors, cameras and entire imaging systems to fulfil scientific/commercial remote sensing despite the difficult conditions on microsatellites. The author has refined these theories by designing, building and exploiting in-orbit five generations of electronic cameras. The major objective of meteorological scale imaging was conclusively demonstrated by the Earth imaging camera flown on the UoSAT-5 spacecraft in 1991. Improved cameras have since been carried by the KITSAT-1 (1992) and PoSAT-1 (1993) microsatellites. PoSAT-1 also flies a medium resolution camera (200 metres) which (despite complete success) has highlighted certain limitations of microsatellites for high resolution remote sensing. A reworked, and extensively modularised, design has been developed for the four camera systems deployed on the FASat-Alfa mission (1995). Based on the success of these missions, this thesis presents many recommendations for the design of microsatellite imaging systems. The novelty of this research programme has been the principle of designing practical camera systems to fit on an existing, highly restrictive, satellite platform, rather than conceiving a fictitious small satellite to support a high performance scanning imager. This pragmatic approach has resulted in the first incontestable demonstrations of the feasibility of remote sensing of the Earth from inexpensive microsatellites