This paper proposes an efficient method to improve image quality based on Context-based enhancement techniques, particularly towards real-time applications in dedicated hardware systems. The main idea is that all the ...
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ISBN:
(纸本)9781467380171
This paper proposes an efficient method to improve image quality based on Context-based enhancement techniques, particularly towards real-time applications in dedicated hardware systems. The main idea is that all the important information of a low-quality an image are combined with a high-quality daytime background image at the same scene to output an image with improved quality, and thus main objects of the low-quality input images can be recognized more easily. In comparison, almost all current context-based enhancement techniques have processed with complex algorithms, thereby being time-consuming and hard to perform in real-time processing when applying into high-resolution images/videos. The developed technique here outperforms these original methods, which is demonstrated by without complex formulas (such as DST and IDST), whereas not only still keeping all the important information of the low-quality nighttime input images, but also limiting problems often existing in context fusion techniques, such as ghosting, haloing and artifact effects. The experimental results demonstrate that our approach has been efficient and gained a better quality of output images in comparison with the results of the Denighting method [8].
Sophisticated computational imaging algorithms require both high performance and good energy-efficiency when executed on mobile devices. Recent trend has been to exploit the abundant data-level parallelism found in ge...
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ISBN:
(纸本)9781509010950
Sophisticated computational imaging algorithms require both high performance and good energy-efficiency when executed on mobile devices. Recent trend has been to exploit the abundant data-level parallelism found in general purpose programmable GPUs. However, for low-power mobile use cases, generic GPUs consume excessive amounts of power. This paper proposes a programmable computational imaging processor with 16-bit half-precision SIMD floating point vector processing capabilities combined with power efficiency of an exposed datapath. In comparison to traditional VLIW architectures with similar computational resources, the exposed datapath reduces the register file traffic and complexity. These and the specific optimizations enabled by the explicit programming model enable extremely good power-performance. When synthesized on a 28nm ASIC technology, the accelerator consumes 71mW of power while running a state-of-the-art denoising algorithm, and occupies only 0.2mm(2) of chip area. For the algorithm, energy usage per frame is 7mJ, which is 10x less than the best found GPU-based implementation.
The proceedings contain 46 papers. The special focus in this conference is on Swarm Intelligence and Its Applications. The topics include: Improving the searching capacity of evolved bat algorithm by the periodic sign...
ISBN:
(纸本)9783319232034
The proceedings contain 46 papers. The special focus in this conference is on Swarm Intelligence and Its Applications. The topics include: Improving the searching capacity of evolved bat algorithm by the periodic signal;evolved bat algorithm with increase-wave strategy;a new digital image compression method using chrestenson transform;intelligent algorithms and their application in electrical impedance tomography;design of multifunctional communication card based on reflective memory;computation of large-scale electric field in free space;an investigation on maximum entropy estimation based on chrestenson transform;a niching genetic algorithm including an inbreeding mechanism for multimodal problems;robust reversible colour image digital watermarking using offset coefficient technique;analysis of movement effectiveness in badminton strokes with accelerometers;a simple and non-invasive measurement method important for conserving large animals underwater;characterization of malware detection on android application;enhancement of preventing application layer based on DDOS attacks by using hidden semi-Markov model;private cloud deployment model for academic environment using cloudstack;two methods for color constancy based on the color correlation matrix;machine learning techniques for myanmar word-sense disambiguation;a graph representative structure for detecting automorphic graphs;a method of wavelength selection of multispectral image for the separation of tumor region;analysis of signal variation based on path loss in LTE network.;automatic response analyzer with multiple choices in classroom using imageprocessing and cards and design and implementation of real time vision system for recognizing features of lane boundary.
Computer vision and image analysis have taken advantage of five decades of intense development. The complexity of the algorithms in this field can now benefit from dramatically increasing computational power to offer ...
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ISBN:
(纸本)9781509030859
Computer vision and image analysis have taken advantage of five decades of intense development. The complexity of the algorithms in this field can now benefit from dramatically increasing computational power to offer viable applications going from embedded systems to cloud computing. This special session proposes three papers dealing with the implementation of computer vision and image analysis applications on embedded systems.
Multi-beam scanning electron microscopy (MBSEM), has been developed to reduce the acquisition time by scanning multiple pixels simultaneously. The signal from the 14 × 14 beams is captured on a camera which reads...
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ISBN:
(纸本)9781467395564
Multi-beam scanning electron microscopy (MBSEM), has been developed to reduce the acquisition time by scanning multiple pixels simultaneously. The signal from the 14 × 14 beams is captured on a camera which reads out the position and intensity for each beam on the sample. But as we work with multiple beams and pixels we need a powerful technique for image acquisition and imageprocessingalgorithms. We use Field Programmable Gate Arrays (FPGA's), often used as an implementation platform for real time image acquisition and processing applications, because their structure is able to exploit spatial and temporal parallelism. This paper presents a technique for dealing with the various constraints of the camera and efficient mapping for image acquisition and processing operations on FPGA.
Todays, the number of vehicles is rapidly increasing. In parallel, the number of ways and traffic signs have increased. As a result of increased traffic signs, the drivers are expected to learn all the traffic signs a...
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Todays, the number of vehicles is rapidly increasing. In parallel, the number of ways and traffic signs have increased. As a result of increased traffic signs, the drivers are expected to learn all the traffic signs and to pay attention to them while driving. A system that can automatically recognize the traffic signs has been need to reduce traffic accidents and to drive more freely. Traffic sign recognition system meet this need. This study includes traffic sign detection and recognition application. In this study, some imageprocessing techniques are used to detect traffic signs and Fuzzy Integral is used to recognize traffic signs. Both more accuracy rate results and low computational cost are obtained in terms of recognition stage by using positive aspects of algorithms taken as input parameters with Fuzzy Integral in the traffic sign recognition system. Experimental results show that proposed method gives high accurate results in a reasonable time.
In this paper, imageprocessingalgorithms designed in Zynq SoC using the Vivado HLS tool are presented and compared with hand-coded designs. In Vivado HLS, the designer has the opportunity to employ libraries similar...
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ISBN:
(纸本)9781509045662
In this paper, imageprocessingalgorithms designed in Zynq SoC using the Vivado HLS tool are presented and compared with hand-coded designs. In Vivado HLS, the designer has the opportunity to employ libraries similar to OpenCV, a library that is well-known and wide used by software designers. The algorithms are compared in terms of area resources in two conditions: using the libraries and not using the libraries. The case studies are Data Binning, a Step Row Filter and a Sobel Filter. These algorithms have been selected because they are very common in the field of imageprocessing and they have high computational complexity. The main benefit of the Vivado HLS tool is the reduction in time-to-market. On the other hand, when a software designer hand-codes the design, the use of imageprocessing libraries similar to OpenCV helps to reduce development time even further because software designers are familiar with them. However, using these kinds of libraries significantly increases the necessary FPGA resources.
Vision-based underwater navigation and object detection requires robust computer vision algorithms to operate in turbid water. Many conventional methods aimed at improving visibility in low turbid water. In this paper...
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ISBN:
(纸本)9781467399623
Vision-based underwater navigation and object detection requires robust computer vision algorithms to operate in turbid water. Many conventional methods aimed at improving visibility in low turbid water. In this paper, we propose a novel contrast enhancement to enhance high turbid underwater images using descattering and color correction. The proposed enhancement method removes the scatter and preserves colors. In addition, as a rule to compare the performance of different image enhancement algorithms, a more comprehensive image quality assessment index Qu is proposed. The index combines the benefits of SSIM index and color distance index. Experimental results show that the proposed approach statistically outperforms state-of-the-art general purpose underwater image contrast enhancement algorithms. The experiment also demonstrated that the proposed method performs well for image classification.
Early forest fire alarm systems are critical in making prompt response in the event of unexpected hazards. Cost-effective cameras, improvements in memory, and enhanced computation power have all enabled the design and...
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ISBN:
(纸本)9781467383189
Early forest fire alarm systems are critical in making prompt response in the event of unexpected hazards. Cost-effective cameras, improvements in memory, and enhanced computation power have all enabled the design and real-time application of fire detecting algorithms using light and small-size embedded surveillance systems. This is vital in situations where the performance of traditional forest fire monitoring and detection techniques are unsatisfactory. This paper presents a forest fire monitoring and detection method with visual sensors onboard unmanned aerial vehicle (UAV). Both color and motion features of fire are adopted for the design of the studied forest fire detection strategies. This is for the purpose of improving fire detection performance, while reducing false alarm rates. Indoor experiments are conducted to demonstrate the effectiveness of the studied forest fire detection methodologies.
Automatic Identification of disease through imageprocessing in biomedical field is the norm of modern era. Ophthalmologists have used several invasive and noninvasive techniques for early detection of disease. OCT is...
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ISBN:
(纸本)9781509018185
Automatic Identification of disease through imageprocessing in biomedical field is the norm of modern era. Ophthalmologists have used several invasive and noninvasive techniques for early detection of disease. OCT is one such noninvasive modality that performs high resolution tomographic imaging in biological systems. OCT images are produced containing speckle noise. Noise is a major factor that decreases image quality, hence degrading performance of noise imageprocessingalgorithms. It is therefore at highest priority to apply effective method for denoising image, before further processing. In this paper we applied Wavelet denoising, bilateral and wiener filter on an OCT images and discuss benefits and drawback of each algorithms. The effectiveness of each algorithm is compared on basis of Signal to noise ratio SNR, peak signal to noise ratio PSNR and Mean square error MSE.
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