In recent years, deep learning has achieved promising success for multimedia quality assessment, especially for image quality assessment (IQA). However, since there exist more complex temporal characteristics in video...
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Traditional single image super-resolution (SISR) methods that focus on solving single and uniform degradation (i.e., bicubic down-sampling), typically suffer from poor performance when applied into real-world low-reso...
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Hybrid-distorted image restoration (HD-IR) is dedicated to restore real distorted image that is degraded by multiple distortions. Existing HD-IR approaches usually ignore the inherent interference among hybrid distort...
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Image quality assessment (IQA) aims to estimate human perception based image visual quality. Although existing deep neural networks (DNNs) have shown significant effectiveness for tackling the IQA problem, it still ne...
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We propose an image coding scheme that compresses image into semantically scalable bitstream using deep neural networks. This scheme is expected to support intelligent analysis when the bitstream is partially decoded,...
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ISBN:
(数字)9781728133201
ISBN:
(纸本)9781728133218
We propose an image coding scheme that compresses image into semantically scalable bitstream using deep neural networks. This scheme is expected to support intelligent analysis when the bitstream is partially decoded, as well as high-fidelity reconstruction of image when the bitstream is completely decoded. We implement such a semantically scalable image coding scheme based on semantic map. In the proposed scheme, the original image is firstly semantically segmented and the semantic map is compressed as the base layer. Then, the original image is segmented into several individual objects according to the semantic map, and each object is coded separately. A recurrent neural network-based encoder is used to compress these objects at several quality levels. At the decoder side, the semantic map can be directly applied for intelligent analysis. A generative adversarial network is used to synthesize a rough image using the semantic map. If user is interested in a certain object, more bits can be transmitted to enhance the quality of the object. Experimental results show that the proposed method achieves comparable compression performance with JPEG2000 at high bit rates, while facilitates intelligent analysis at low bit rates.
Quality assessment of omnidirectional images has become increasingly urgent due to the rapid growth of virtual reality applications. Different from traditional 2D images and videos, omnidirectional contents can provid...
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The circular synthetic aperture radar (SAR) can observe the experimental scene from all angles. The backscatter intensity of the target in the scene can be obtained. Different targets in the imaging scene show differe...
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ISBN:
(纸本)9781665468893
The circular synthetic aperture radar (SAR) can observe the experimental scene from all angles. The backscatter intensity of the target in the scene can be obtained. Different targets in the imaging scene show different amplitude characteristics. For example, significant targets such as buildings and oil tanks show strong response characteristics at certain angles, and secondly, weak response characteristics for targets is shown such as grass and ground. In this article, the omnidirectional scattering intensity data of the target obtained from the radar is used to analyze the amplitude characteristics, and the model is established for different targets to obtain the final result. The fuzzy C-means (FCM) model combined with neighborhood information is used to analyze the target amplitude characteristics. The amplitude characteristics of the target are divided into two categories: strong response and weak response for analysis. The initial two types of cluster centers are set for iteration and finally the target amplitude characteristic reference values at different angles are obtained. C-band circular SAR data is used to validate our method. As a result, the amplitude characteristics of the whole scene using membership degree can be described.
Most existing image restoration networks are designed in a disposable way and catastrophically forget previously learned distortions when trained on a new distortion removal task. To alleviate this problem, we raise t...
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Leader-following formation analysis problem for a second-order nonlinear multi-agent system(MAS) with input saturation is investigated in this paper. And the impulsive formation control algorithm is introduced in the ...
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Leader-following formation analysis problem for a second-order nonlinear multi-agent system(MAS) with input saturation is investigated in this paper. And the impulsive formation control algorithm is introduced in the designed protocol which only works at the impulse times. Owing to the real-world limited communication channels, input saturation is considered in the impulsive controller. Furthermore, based on Lyapunov stability theories, Kronecker properties, eigenvalue and so on, some sufficient conditions that guarantee the leader-following consensus of MAS are obtained. Lastly, several simulations are worked out to verify the correctness and effectiveness of the theoretical results.
The 3D local surface description is a crucial aspect within the domain of computer vision. This paper advances a novel approach that leverages a repeatable local reference frame (LRF) and a cumulative multi-feature im...
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