image super-resolution (ISR) is an important imageprocessing technology to improve image resolution in computer vision tasks. The purpose of this paper is to study the super-resolution reconstruction of single image ...
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imageprocessing technology had a beneficial impact on the material processing process. For purpose of acquiring the droplet images of the metal transfer process, high speed camera/laser system was applied to acquire ...
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With emergence of the smart and intuitive interfaces during the past few years the need for robust and reliable algorithms rises. Many methods have been proposed for image segmentation, and particularly for static ges...
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ISBN:
(纸本)9789531841917
With emergence of the smart and intuitive interfaces during the past few years the need for robust and reliable algorithms rises. Many methods have been proposed for image segmentation, and particularly for static gesture recognition. In this article, using Microsoft Kinect sensor, we attempt to analyze and compare three selected algorithms for image segmentation intended for static gesture recognition, namely Convexity Defects, K-Curvature and Part-based Hand Gesture Recognition.
This paper mainly introduces three typical transform domain methods for image coding. Design programs of image transform domain coding algorithms based on DFT, DCT and WHT. For different input images, the paper compar...
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Methodology and stages of data processing in multichannel airborne radar imaging systems are considered. It is shown that data fusion in such systems requires special techniques, algorithms, and software for image pro...
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ISBN:
(纸本)0819436771
Methodology and stages of data processing in multichannel airborne radar imaging systems are considered. It is shown that data fusion in such systems requires special techniques, algorithms, and software for imageprocessing and information retrieval. Some approaches and methods are proposed. The results are demonstrated for simulated and real images.
Lane detection plays a crucial role for Advanced Driver Assitance System (ADAS) or autonomous driving applications. Literature shows a lot of lane detection algorithms can work in real time with good results. However,...
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ISBN:
(纸本)9781479983391
Lane detection plays a crucial role for Advanced Driver Assitance System (ADAS) or autonomous driving applications. Literature shows a lot of lane detection algorithms can work in real time with good results. However, they require much computer processing and cannot be embedded in a vehicle ECU without deep software optimizations. In this paper, we discuss the embeddability of lane detection algorithms by comparing state-of-the-art algorithms in terms of functional performance and computational timing. We identify what essential parts of lane detection are time consuming, and show these parts can be computed in real time on embedded systems.
image de-noising in the spatial-temporal domain has been a problem studied in-depth in the field of digital imageprocessing. However complexity of algorithms often leads to high hardware resource usage, or computatio...
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ISBN:
(纸本)9780819494283
image de-noising in the spatial-temporal domain has been a problem studied in-depth in the field of digital imageprocessing. However complexity of algorithms often leads to high hardware resource usage, or computational complexity and memory bandwidth issues, making their practical use impossible. In our research we attempt to solve these issues with an optimized implementation of a practical spatial-temporal de-noising algorithm Spatial-temporal filtering was performed in Bayer RAW data space, which allowed us to benefit from predictable sensor noise characteristics and reduce memory bandwidth requirements. The proposed algorithm efficiently removes different kinds of noise in a wide range of signal to noise ratios. In our algorithm the local motion compensation is performed in Bayer RAW data space, while preserving the resolution and effectively improving the signal to noise ratios of moving objects. The main challenge for the use of spatial-temporal noise reduction algorithms in video applications is the compromise between the quality of the motion prediction and the complexity of the algorithm and required memory bandwidth In photo and video applications it is very important that moving objects should stay sharp, while the noise is efficiently removed in both the static background and moving objects. Another important use case is the case when background is also non-static as well as the foreground where objects are also moving. Taking into account the achievable improvement in PSNR (on the level of the best known noise reduction techniques, like VBM3D) and low algorithmic complexity, enabling its practical use in commercial video applications, the results of our research can be very valuable.
Availability of hardware implementations of super-resolution image reconstruction algorithms is limited mostly by their logical and memory requirements. This is also the case for other imageprocessingalgorithms such...
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ISBN:
(纸本)9781467372282
Availability of hardware implementations of super-resolution image reconstruction algorithms is limited mostly by their logical and memory requirements. This is also the case for other imageprocessingalgorithms such as hyperspectral, image compression, image coding, video coding. In previous publications we have introduced a new execution flow that tackles the problem of high memory requirements of a restoration-interpolation super-resolution kernel by carrying out processing in a macroblock-by-macroblock manner. In this work we present the modelling framework used for the evaluation of the proposed execution flow. The modelling process is presented in a step-by-step manner by means of a real-life example of implementation of super-resolution image reconstruction with description of the choices made at every stage and explanation of the reasoning behind. In the presented case the use of the proposed frame-work led to a hardware implementation with real-time capabilities. This frame-work can be applied to similar algorithms, helping system designers in achieving better work organization and efficiency.
Edge detection of images is a classical problem in computer vision and imageprocessing. The key of edge detection is the choice of threshold;the choice of threshold directly determines the results of edge detection. ...
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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)9781509045655
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.
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