Image Communication

With the prevalence of accessible depth sensors, dynamic skeletons have attracted much attention as a robust modality for action recognition. Convolutional neural networks (CNNs) excel at modeling local relations within local receptive ...

• Spatial–temporal graph interaction network is proposed.
• A fully connected ...

Existing single image haze removal algorithms could suffer from noise amplification in sky regions and possible color distortion in restored images due to noise in haze images. In this paper, a simple pre-processing tool is introduced ...

• The proposed pre-processing tool is simple but effective.
• The algorithm can ...

In this paper, we present an efficient and distinctive local descriptor, namely block intensity and gradient difference (BIGD). In an image patch, we randomly sample multi-scale block pairs and utilize the intensity and gradient ...

• We present a local descriptor called block intensity and gradient difference BIGD.

Sparse representation (SR) has been widely used in image fusion in recent years. However, source image, segmented into vectors, reduces correlation and structural information of texture with conventional SR methods, and extracting ...

• A multi-modality medical image fusion method based on a novel sparse representation (SR) so-called ASeDiL and Gabor energy in non-subsampled contourlet ...

Sparse coding based-methods show great effectiveness in single image super-resolution (SR). Existing methods generally use only synthesis sparse coding. However, the analysis sparse coding model, which is an alternative to the ...

• We first introduce synthesis and analysis sparse coding simultaneously into a training model for single image SR problem.

Many image co-segmentation algorithms have been proposed over the last decade. In this paper, we present a new dataset for evaluating co-segmentation algorithms, which contains 889 image groups with 18 images in each and the pixel-wise ...

In the state-of-the-art human–computer interaction (HCI) systems, gestures feature is more intuitive, natural and, easy-to-acquire than the other visual features. Due to the high descriptiveness of hand movements and the scarcity of ...

• Feature maps in the same size outputted by different layers are fused, which can effectively retain the key information on a small scale.

The research of video-based sports movement analysis technology has an important application value. The introduction of digital video, human–computer interaction and other technologies in sports training can greatly improve training ...

• We introduced a spatial and temporal scoring mechanism for video analysis to define and extract the key video frames.

Recognizing human action under uncontrolled environment is significant for human–computer interaction (HCI), especially for virtual reality game, sports narrative, and video captioning. Nowadays, however, human action recognition ...

• We fuse motion features, posture information and skeleton sequence to describe human actions.

Image quality assessment (IQA) is an indispensable technique in computer vision and pattern recognition Existing deep IQA methods have achieved remarkable performance. As far as we know, these deep learning-based IQA algorithms lack an ...

• The proposed framework is adaptive for IQA on images with varying size.
• We ...

Aiming at the problem that the remote sensing image quality evaluation models with manually extracted features lack robustness and generality, this paper proposes a 3D CNN-based architecture and nuclear power plant for accurate remote ...

Image quality assessment (IQA) attempts to quantify the quality-aware visual attributes perceived by humans. They can be divided into subjective and objective image quality assessment. Subjective IQA algorithms rely on human judgment ...

• We leverage structural cues to calculate the similarity between the original image and the test one.

In order to alleviate the overfitting problem caused by image quality evaluation (IQA) model learning under intolerably small dataset, this paper proposes a multi-feature fusion-based deep architecture for hyperspectral image quality ...

• The features descriptive to hyperspectral images are collaboratively and seamlessly integrated.

The standard no-reference video quality assessment (NR-VQA) is designed for a specific type of distortion. It quantifies the visual quality of a distorted video without the reference one. Practically, there is a deviation between the ...

• The proposed IQA method is non-reference VQA method.
• The problems caused by ...

To improve image quality assessment (IQA) methods, it is believable that we have to extract image features that are highly representative to human visual perception. In this paper, we propose a novel IQA algorithm by leveraging an ...

• We proposed a simple but efficient non-reference IQA algorithm.
• We introduced a ...

In order to improve the visual appearance of defogged of aerial images, in this work, a novel defogging algorithm based on conditional generative adversarial network is proposed. More specifically, the training process is carried out ...

• We propose a defogged image quality assessment algorithm based on rank learning.

Hyperspectral image quality assessment (HIQA) is an indispensable technique in both academic and industry domain However, HIQA is still a challenging task since those fine-grained and quality-aware visual details are difficult to be ...

• The designed mid-level features can better represent attributes of hyperspectral images.