Atmospheric scattering model is the main method of image defogging. Aiming at the defects of the existing defogging algorithms in different aspects, this paper puts forward some improvement measures based on the analy...
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ISBN:
(数字)9781728196688
ISBN:
(纸本)9781728196695
Atmospheric scattering model is the main method of image defogging. Aiming at the defects of the existing defogging algorithms in different aspects, this paper puts forward some improvement measures based on the analysis of the defects of the existing defogging methods. In view of the irrationality of estimation of atmospheric light and atmospheric scattering coefficient, a method of locating atmospheric light region based on edge extraction and a method of selecting atmospheric scattering coefficient based on fog concentration are proposed. The estimation of depth of field and transmittance is improved. Finally, adaptive contrast enhancement is carried out for foggy image. The effectiveness of the proposed method is verified by comparative experiments.
Triplet loss has been proposed to increase the inter-class distance and decrease the intra-class distance for various tasks of image recognition. However, for facial expression recognition (FER) problem, the fixed mar...
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ISBN:
(纸本)9781538662496
Triplet loss has been proposed to increase the inter-class distance and decrease the intra-class distance for various tasks of image recognition. However, for facial expression recognition (FER) problem, the fixed margin parameter does not fit the diversity of scales between different expressions. Meanwhile, the strategy of selecting the hardest triplets can introduce noisy guidance information since various persons may present significantly different expressions. In this work, we propose a new triplet loss based on class-aware margins and outlier-suppressed triplet for FER, where each pair of expressions, e.g. 'happy' and 'fear', is assigned with an adaptive margin parameter and the abnormal hard triplets are discarded according to the feature distance distribution. Experimental results of the proposed triplet loss on the FER2013 and CK+ expression databases show that the proposed network achieves much better accuracy than the original triplet loss and the network without using the proposed strategies, and competitive performance compared with the state-of-the-art algorithms.
In digital imageprocessing, noise suppression from the original signal is still considered as biggest challenge till today. image denoising refers to the process in which it evaluates the unknown signal from the avai...
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ISBN:
(纸本)9789811307614;9789811307607
In digital imageprocessing, noise suppression from the original signal is still considered as biggest challenge till today. image denoising refers to the process in which it evaluates the unknown signal from the available noisy signal. Several algorithms are existing, which are proposed by other authors for denoising of an image like Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), etc. This paper contributes itswork by discussing the significant work done in the area of image denoising along with advantages and disadvantages. After a brief discussion, classification of image denoising techniques is explained. A comparative analysis of various image denoising methods is also performed, which will help researchers in the image denoising area. The objective of this review paper is to provide functional knowledge of image denoising methods in a nutshell for applications using images to provide an ease for selecting the ideal strategy according to the necessity.
Many machine learning algorithms, like Convolutional Neural Networks (CNNs), have excelled in imageprocessing tasks;however, they have many practical limitations. For one, these systems require large datasets that ac...
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ISBN:
(纸本)9781728119854
Many machine learning algorithms, like Convolutional Neural Networks (CNNs), have excelled in imageprocessing tasks;however, they have many practical limitations. For one, these systems require large datasets that accurately represent the sample distribution in order to optimize performance. Secondly, they have difficulty transferring previously learned knowledge when evaluating data from slightly different sample distributions. To overcome these drawbacks, we propose a recurrent kernel-based approach for imageprocessing using the Kernel Adaptive Autoregressive Moving Average algorithm (KAARMA). KAARMA minimizes the amount of training data required by using the Reproducing Kernel Hilbert Space to build inference into the system. The recurrent nature of KAARMA additionally allows the system to better learn the spatial correlations in the images through one-shot or near oneshot learning. We demonstrate KAARMA's superiority for small-sample image classification using the JAFFE Face Dataset and the UCI hand written digit dataset.
Frequency modulation continuation wave circular synthetic aperture radar (FMCW CSAR) imaging can’t focus imaging,because of the target scattering coefficient to change caused by large synthetic aperture. The sub-aper...
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The problem of algorithm synthesis for processing of the signals at the output of a spatially distributed antenna system for the formation of radio images from aerospace carriers has been solved. In order to synthesiz...
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ISBN:
(数字)9781728155661
ISBN:
(纸本)9781728155678
The problem of algorithm synthesis for processing of the signals at the output of a spatially distributed antenna system for the formation of radio images from aerospace carriers has been solved. In order to synthesize the optimal algorithm, the maximum likelihood method was used. As a result of analyzing the physical nature of the signal processing operations, a transition to the quasi-optimal processing, which simplifies the technical implementation of the algorithm, is proposed. The main feature of this algorithm lies in the fact is that it allows to receive a radio image in the direction of the nadir within the range of angles that is currently not visible by the radars from aerospace carriers. In this range of angles, an image is usually formed by optical means. A scheme of the radar complex has been developed and modeling of radio image formation has been carried out in accordance with the algorithm.
In this paper, we explore how to design lightweight CNN architecture for embedded computing systems. We propose L-Mobilenet model for ZYNQ based hardware platform. L-Mobilenet can adapt well to hardware computing and ...
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ISBN:
(纸本)9781538662496
In this paper, we explore how to design lightweight CNN architecture for embedded computing systems. We propose L-Mobilenet model for ZYNQ based hardware platform. L-Mobilenet can adapt well to hardware computing and accelerating, and its network structure is inspired by the state-of-the-art work of Inception-Resnet and Mobilenet-V2, which can effectively reduce parameters and delay while maintaining the accuracy of inference. We deploy our L-Mobilenet model to GPU and ZYNQ embedded platform for fully evaluating the performance of our design. By measuring with cifar10 and cifar100 datasets, L-Mobilenet model is able to gain 3x speed up and 3.7x fewer parameters than MobileNet-V2 while maintaining a similar accuracy. It also can obtain 2x speed up and 1.5x fewer parameters than Shufflenet-V2 while maintaining the same accuracy. Experiments show that our network model can obtain better performance because of the special considerations for hardware accelerating and software-hardware co-design strategies in our L-Mobilenet bottleneck architecture.
This work proposes the use of Genetic algorithms (GA) to identify the area of the breast from the background in thermographic breast images. The proposed method uses color information, a fitness function based on card...
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ISBN:
(数字)9781728175393
ISBN:
(纸本)9781728175409
This work proposes the use of Genetic algorithms (GA) to identify the area of the breast from the background in thermographic breast images. The proposed method uses color information, a fitness function based on cardioids, and GA. This is the first work in the literature to propose a Region of Interest (ROI) extraction based on GA and cariods. ROI extraction can improve the accuracy of cancer detection and assist with the standardization of acquisition protocols. The method is able to successfully separate the breast region in 52 out of 58 images, while being fully automatic, and not requiring manual selection of seed points.
This paper presents the study and the evaluation of GPS/GNSS techniques combined with advanced imageprocessingalgorithms for the precise detection, positioning and tracking of distressed humans. In particular, the i...
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ISBN:
(数字)9781728142784
ISBN:
(纸本)9781728142791
This paper presents the study and the evaluation of GPS/GNSS techniques combined with advanced imageprocessingalgorithms for the precise detection, positioning and tracking of distressed humans. In particular, the issue of human detection on both terrestrial and marine environments, as the human silhouette in a marine environment may differ substantially from a land one, is addressed. A robust approach, including an adaptive distressed human detection algorithm running every N input image frames combined with a much faster human tracking algorithm, is proposed. Real time or near-real-time distressed human detection rates, under several illumination and background conditions, can be achieved using a single, low cost day/night NIR camera. It is mounted onboard a fully autonomous UAV for Search and Rescue (SAR) missions. Moreover, the collection of a novel dataset, suitable for training the computer vision algorithms is also presented. Details about both hardware and software configuration as well as the assessment of the proposed approach performance are discussed. Last, a comparison of the proposed approach to other human detection methods used in the literature is presented.
In this paper, we present a simple and effective algorithm of lossless image compression to save coding space. Dynamic block encoding is applied, to reduce the coding bit via the reduction of the image spatial correla...
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ISBN:
(数字)9781728168968
ISBN:
(纸本)9781728168975
In this paper, we present a simple and effective algorithm of lossless image compression to save coding space. Dynamic block encoding is applied, to reduce the coding bit via the reduction of the image spatial correlation. The original image is divided into uniform blocks with a proper size, to achieve a good intra-block correlation, then a reference rule is applied to decorrelate each block and squeeze the extra coding bit of each block, resulting in effective compression. Compared with the traditional unified encoding, the proposed algorithm optimizes the coding space via intra-block correlation, and the iteration compression can be performed further to squeeze inter-block correlation fully. Compression ratios of 1.807 and 1.857 are achieved for a single and three iterations, respectively, with a block size of 4. Due to the simple and efficient reference rule, the proposed algorithm also avoids complex mathematical computation in the traditional image compression methods.
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