The imageprocessing mainly includes the image compression, the image filtering, the image sampling, the image segmentation and the image analysis. At present, the imageprocessing has an important role in many practi...
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ISBN:
(纸本)9783030152352;9783030152345
The imageprocessing mainly includes the image compression, the image filtering, the image sampling, the image segmentation and the image analysis. At present, the imageprocessing has an important role in many practical fields, such as the image recognition and the face recognition and so on. Its technical core is the imageprocessing. With the continuous expansion of the imageprocessing scale in these areas and the continuous improvement of the real-time performance requirements, how to improve the performance of the imageprocessingalgorithms has become a current research hotspot.
The theory of correlation filters does not make any assumptions about the sensor or image format. Thus the same class of algorithms is readily applicable to multiple sensor environments such as IR, SAR, LADAR, or CCD ...
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ISBN:
(纸本)081942921X
The theory of correlation filters does not make any assumptions about the sensor or image format. Thus the same class of algorithms is readily applicable to multiple sensor environments such as IR, SAR, LADAR, or CCD (visual). The advantage is that the same theory is valid for multiple sensor applications, the processing steps are common (and code) are re-usable in different sensor platforms, and the algorithms are rapidly re-trainable. The paper points out the key benefits resulting from the general formulation and solution resulting from the correlation approach to ATR.
To deal with the problem of restoring degraded images with non-Gaussian noise, this paper proposes a novel cooperative neural fusion regularization (CNFR) algorithm for image restoration. Compared with conventional re...
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To deal with the problem of restoring degraded images with non-Gaussian noise, this paper proposes a novel cooperative neural fusion regularization (CNFR) algorithm for image restoration. Compared with conventional regularization algorithms for image restoration, the proposed CNFR algorithm can relax need of the optimal regularization parameter to be estimated. Furthermore, to enhance the quality of restored images, this paper presents a cooperative neural fusion (CNF) algorithm for image fusion. Compared with existing signal-level image fusion algorithms, the proposed CNF algorithm can greatly reduce the loss of contrast information under blind Gaussian noise environments. The performance analysis shows that the proposed two neural fusion algorithms can converge globally to the robust and optimal image estimate. Simulation results confirm that in different noise environments, the proposed two neural fusion algorithms can obtain a better image estimate than several well known image restoration and image fusion methods.
Recent years have witnessed a growing interest in developing objective image quality assessment (IQA) algorithms that can measure the image quality consistently with subjective evaluations. For the full reference (FR)...
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ISBN:
(纸本)9781467325332;9781467325349
Recent years have witnessed a growing interest in developing objective image quality assessment (IQA) algorithms that can measure the image quality consistently with subjective evaluations. For the full reference (FR) IQA problem, great progress has been made in the past decade. On the other hand, several new large scale image datasets have been released for evaluating FR IQA methods in recent years. Meanwhile, no work has been reported to evaluate and compare the performance of state-of-the-art and representative FR IQA methods on all the available datasets. In this paper, we aim to fulfill this task by reporting the performance of eleven selected FR IQA algorithms on all the seven public IQA image datasets. Our evaluation results and the associated discussions will be very helpful for relevant researchers to have a clearer understanding about the status of modern FR IQA indices. Evaluation results presented in this paper are also online available at http://***/linzhang/IQA/***.
We have developed a novel approach to performing automatic detection of concealed threat objects in passive MMW imagery of people scanned in a portal setting. It is applicable to the significant class of imaging scann...
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ISBN:
(纸本)9780819471390
We have developed a novel approach to performing automatic detection of concealed threat objects in passive MMW imagery of people scanned in a portal setting. It is applicable to the significant class of imaging scanners that use the protocol of having the subject rotate in front of the camera in order to image them from several closely spaced directions. Customary methods of dealing with MMW sequences rely on the analysis of the spatial images in a frame-by-frame manner, with information extracted from separate frames combined by some subsequent technique of data association and tracking over time. We contend that the pooling of information over time in traditional methods is not as direct as can be and potentially less efficient in distinguishing threats from clutter. We have formulated a more direct approach to extracting information about the scene as it evolves over time. We propose an atypical spatio-temporal arrangement of the MMW image data - to which we give the descriptive name Row Evolution image (REI) sequence. This representation exploits the singular aspect of having the subject rotate in front of the camera. We point out which features in REIs are most relevant to detecting threats, and describe the algorithms we have developed to extract them. We demonstrate results of successful automatic detection of threats, including ones whose faint image contrast renders their disambiguation from clutter very challenging. We highlight the ease afforded by the REI approach in permitting specialization of the detection algorithms to different parts of the subject body. Finally, we describe the execution efficiency advantages of our approach, given its natural fit to parallel processing.
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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We propose a new ballistic imaging method that is capable of imaging an object through an intense scattering medium. In this method, a femtosecond supercontinuum and a roundabout spatial gate were used to suppress spe...
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We propose a new ballistic imaging method that is capable of imaging an object through an intense scattering medium. In this method, a femtosecond supercontinuum and a roundabout spatial gate were used to suppress speckles and filter background noise, respectively. The roundabout spatial gate extracts ballistic light and avoids low- pass spatial filtering to ensure the high resolution of images. The experimental results showed that even when the optical depth of the scattering medium reached 17, the images extracted by the method had improved identifiability and contrast. (C) 2017 Optical Society of America
This study applies genetic algorithms to select financial statement variables which are used to predict the direction of one-year-ahead earnings change. To evaluate the forecasting ability of GA-based-linear discrimin...
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ISBN:
(纸本)9781424409907
This study applies genetic algorithms to select financial statement variables which are used to predict the direction of one-year-ahead earnings change. To evaluate the forecasting ability of GA-based-linear discriminant analysis (GA-LDA), this study compares it with probabilistic neural network and decision tree model. The experiment results show that the GA-LDA model outperforms other classification methods.
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.
image registration is a very common and important problem in several fields such as medical imaging, computer vision. simulation. etc. The aim of this contribution is to present a new mathematical partial differential...
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ISBN:
(纸本)0819441880
image registration is a very common and important problem in several fields such as medical imaging, computer vision. simulation. etc. The aim of this contribution is to present a new mathematical partial differential equation (PDE)-model for the registration of two-dimensional (2D) and three-dimensional (3D). eventually noisy. images. Estimating the registration between two image data sets is here formulated as a motion estimation and evolution problem. Moreover we shortly review the PDE approaches which originated the proposed model. The model is based on ideas introduced for processing of space-time image sequences. The proposed algorithm can deal with small and large deformations. it also works in presence of noise and it is very fast. Computational results in processing of a variety of images including synthetic and medical images are presented.
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