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Deep Convolutional Neural Network Based on Multi-Scale Feature Extraction for image Denoising

Deep Convolutional Neural Network Based on Multi-Scale Featu...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Zhang, Jing Sang, Liu Wan, Zekang Wang, Yuchen Li, Yunsong Xidian Univ State Key Lab Integrated Serv Networks Xian Peoples R China

ISBN: (纸本)9781728180687

With the development of deep learning, many methods on image denoising have been proposed processing images on a fixed scale or multi-scale which is usually implemented by convolution or deconvolution. However, excessive scaling may lose image detail information, and the deeper the convolutional network the easier to lose network gradient. Diamond Denoising Network (DmDN) is proposed in this paper, which mainly based on a fixed scale and meanwhile considering the multi-scale feature information by using the Diamond-Shaped (DS) module to deal with the problems above. Experimental results show that DmDN is effective in image denoising.

关键词： image denoising multi-scale convolutional network diamond

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Towards Universal GAN image Detection

Towards Universal GAN Image Detection

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Cozzolino, Davide Gragnaniello, Diego Poggi, Giovanni Verdoliva, Luisa Univ Federico II Naples Naples Italy

ISBN: (纸本)9781728185514

The ever higher quality and wide diffusion of fake images have spawn a quest for reliable forensic tools. Many GAN image detectors have been proposed, recently. In real world scenarios, however, most of them show limited robustness and generalization ability. Moreover, they often rely on side information not available at test time, that is, they are not universal. We investigate these problems and propose a new GAN image detector based on a limited sub-sampling architecture and a suitable contrastive learning paradigm. Experiments carried out in challenging conditions prove the proposed method to be a first step towards universal GAN image detection, ensuring also good robustness to common image impairments, and good generalization to unseen architectures.

关键词： Fake detection

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UGNet: Underexposed images Enhancement Network based on Global Illumination Estimation

UGNet: Underexposed Images Enhancement Network based on Glob...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Fang, Yuan Zhu, Wenzhe Zhu, Qing Beijing Univ Technol Sch Software Engn Beijing Peoples R China

ISBN: (纸本)9781728180687

This paper proposes a new neural network for enhancing underexposed images. Instead of the decomposition method based on Retinex theory, we introduce smooth dilated convolution to estimate global illumination of the input image, and implement an end-to-end learning network model. Based on this model, we formulate a multi-term loss function that combines content, color, texture and smoothness losses. Our extensive experiments demonstrate that this method is superior to other methods in underexposed image enhancement. It can cover more color details and be applied to various underexposed images robustly.

关键词： underexposed enhancement global illumination estimation image restoration smooth dilated convolution

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AnomalyHop: An SSL-based image Anomaly Localization Method

AnomalyHop: An SSL-based Image Anomaly Localization Method

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Zhang, Kaitai Wang, Bin Wang, Wei Sohrab, Fahad Gabbouj, Moncef Kuo, C-C Jay Univ Southern Calif Ming Hsieh Dept Elect & Comp Engn Los Angeles CA 90007 USA Tampere Univ Dept Comp Sci Tampere Finland

ISBN: (纸本)9781728185514

An image anomaly localization method based on the successive subspace learning (SSL) framework, called AnomalyHop, is proposed in this work. AnomalyHop consists of three modules: 1) feature extraction via successive subspace learning (SSL), 2) normality feature distributions modeling via Gaussian models, and 3) anomaly map generation and fusion. Comparing with state-of-the-art image anomaly localization methods based on deep neural networks (DNNs), AnomalyHop is mathematically transparent, easy to train, and fast in its inference speed. Besides, its area under the ROC curve (ROC-AUC) performance on the MVTec AD dataset is 95.9%, which is among the best of several benchmarking methods.

关键词： image anomaly localization successive subspace learning

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A Comparative Analysis of Nerve Vessels Enhancement and Segmentation Techniques Through Edge Detection on Retinal Fundus images

A Comparative Analysis of Nerve Vessels Enhancement and Segm...

引用

3rd International conference on Advancements in Smart Computing and Information Security, ASCIS 2024

作者： Durga, N. KeranaHanirex, D. Muthukumaravel, A. Department of Computer Applications Bharath Institute of Higher Education and Research Tamil Nadu Chennai India Department of MCA Bharath Institute of Higher Education and Research Tamil Nadu Chennai India

ISBN: (纸本)9783031863011

Diagnosing wider disease in retina is more significant in Ophthalmology. Using image processing techniques to identify the retinal diseases has proven more precise than other technology implementations, rapidly. Certain disorder identifications lowers the quality with respect to the limiting capacities and diagnosing them. Irrespective of several algorithms and researches the issue remains unsolved on the retinal disease identifications using image processing. Where huge number of observations turned negative with retinal color images, which in turn formulated an enhanced technique that is solely focuses on the green component of the retinal image. Corona virus spread during the year 2019 is predicted to have allied with the variations in the nerve vessel, that is seen into the partitioned eye fundus with the patients in the process of detecting the variations in the retinal via image processing which is also used to assess the potential correlation over medical ***, the retinal image of the eye is pre-processed which is further processed by identifying the presence of the pictorial particulars using contrast improvisation and histogram equalization, CLAHE. Secondly by removing the noise from the image, using WMF (www mmmm ffff). Upon comparison with filters like median, wiener etc., WMF is proved to be the best from the results obtained in this proposed research work. Finally, retinal images were segmented with the nerve cells in the retinal images of Covid-19 infected individuals using SOBCAN (SSSooobbb ccc aaa nnn) methodology. The fundus images and performance was evaluated based on parameters including MSE, PSNR and SSIM. The results were compared with other technologies like sobel, canny etc., and concludes that the proposed methods’ formulated outcome outperforms the equivalent enhancement method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： image correlation

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No-reference Stereoscopic image Quality Assessment Based on Parallel Multi-scale Perception

No-reference Stereoscopic Image Quality Assessment Based on ...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Zhang, Ziyi Li, Sumei Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781665475921

With the rapid development of 3D technologies, effective no-reference stereoscopic image quality assessment (NR-SIQA) methods are in great demand. In this paper, we propose a parallel multi-scale feature extraction convolution neural network (CNN) model combined with novel binocular feature interaction consistent with human visual system (HVS). In order to simulate the characteristics of HVS sensing multi-scale information at the same time, parallel multi-scale feature extraction module (PMSFM) followed by compensation information is proposed. And modified convolutional block attention module (MCBAM) with less computational complexity is designed to generate visual attention maps for the multi-scale features extracted by the PMSFM. In addition, we employ cross-stacked strategy for multi-level binocular fusion maps and binocular disparity maps to simulate the hierarchical perception characteristics of HVS. Experimental results show that our method is superior to the state-of-the-art metrics and achieves an excellent performance.

关键词： no-reference stereoscopic image quality assessment (NR-SIQA) convolution neural network (CNN) human visual system (HVS)

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Security and Forensics Exploration of Learning-based image Coding

Security and Forensics Exploration of Learning-based Image C...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Bhowmik, Deepayan Elawady, Mohamed Nogueira, Keiller Univ Stirling Div Comp Sci & Math Stirling FK9 4LA Scotland

ISBN: (纸本)9781728185514

Advances in media compression indicate significant potential to drive future media coding standards, e.g., Joint Photographic Experts Group's learning-based image coding technologies (JPEG AI) and Joint Video Experts Team's (JVET) deep neural networks (DNN) based video coding. These codecs in fact represent a new type of media format. As a dire consequence, traditional media security and forensic techniques will no longer be of use. This paper proposes an initial study on the effectiveness of traditional watermarking on two state-of-the-art learning based image coding. Results indicate that traditional watermarking methods are no longer effective. We also examine the forensic trails of various DNN architectures in the learning based codecs by proposing a residual noise based source identification algorithm that achieved 79% accuracy.

关键词： Media forensics security learning based image coding JPEG AI DNN watermarking source identification

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DesnowFormer: an effective transformer-based image desnowing network

DesnowFormer: an effective transformer-based image desnowing...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Zhang, Ting Jiang, Nanfeng Lin, Junhong Lin, Jielian Zhao, Tiesong Fuzhou Univ Coll Phys & Informat Engn Fujian Key Lab Intelligent Proc & Wireless Transm Fuzhou Peoples R China

ISBN: (纸本)9781665475921

Single image desnowing is an important and challenge task for lots of computer vision applications, such as visual tracking and video surveillance. Although existing deep learning-based methods have achieved promising results, most of them rely on the local deep features and neglect global relationship information between the local regions. Therefore, inevitably leading to over-smooth or detail loss results. To solve this issue, we design a UNet-based end-to-end architecture for image desnowing. Specially, to better characterize global information and preserve image detail, we combine Window-based Self-Attention (WSA) transformer block with Residue Spatial Attention (RSA) to build basic unit of our network. Besides, to protect the structure of the image effectively, we also introduce a Residue Channel (RC) loss to guide high-quality image restoration. Extensive experimental results on both synthetic and real-world datasets demonstrate that the proposed model achieves new state-of-the-art results.

关键词： image Desnowing Transformer block Residual Spatial Attention

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Alignment of image-Text and Video-Text Datasets 31

Alignment of Image-Text and Video-Text Datasets

引用

31st IEEE conference on Signal processing and communications Applications (SIU)

作者： Ozkose, Yunus Emre Gokce, Zeynep Duygulu, Pinar Hacettepe Univ Bilgisayar Muhendisligi Ankara Turkiye

ISBN: (纸本)9798350343557

In this study, the alignment of video-text and image-text datasets is studied. Firstly, similarities are calculated over the texts in the two data sets. A retrieval setup with visual similarities is then applied to the subset which is created via calculated text similarities. A BERT-based embedding vector method is applied to the raw and pure texts. As a visual feature, object-based and CLIP-based methods are used to define video frames. According to the results, alignment with CLIP features achieves the best results in the subset created by filtering using raw text.

关键词： dataset alignment deep learning machine learning

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Perceptual Evaluation of Pre-processing for Video Transcoding

Perceptual Evaluation of Pre-processing for Video Transcodin...

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IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Huang, Shiyu Luo, Ziyuan Xu, Jiahua Zhou, Wei Chen, Zhibo Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei Peoples R China

ISBN: (纸本)9781728185514

Recently, the pre-processed video transcoding has attracted wide attention and has been increasingly used in practical applications for improving the perceptual experience and saving transmission resources. However, very few works have been conducted to evaluate the performance of pre-processing methods. In this paper, we select the source (SRC) videos and various pre-processing approaches to construct the first Pre-processed and Transcoded Video Database (PTVD). Then, we conduct the subjective experiment, showing that compared with the video sent to the codec directly at the same bitrate, the appropriate pre-processing methods indeed improve the perceptual quality. Finally, existing image/video quality metrics are evaluated on our database. The results indicate that the performance of the existing image/video quality assessment (IQA/VQA) approaches remain to be improved. We will make our database publicly available soon.

关键词： Video quality assessment Subjective evaluation Database Pre-processing for video transcoding

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