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检索条件"任意字段=Conference on Visual Communications and Image Processing 2004"

共 4342 条记录，以下是271-280 订阅

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Using Regularity Unit As Guidance For Summarization-Based image Resizing

Using Regularity Unit As Guidance For Summarization-Based Im...

引用

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

作者： Hsiao, Fang-Tsung Lin, Yi-Hsien Lu, Yi-Chang Natl Taiwan Univ Dept Elect Engn Taipei 10617 Taiwan Natl Taiwan Univ Grad Inst Elect Engn Taipei 10617 Taiwan

ISBN: (纸本)9781728185514

In this paper, we propose a novel algorithm for summarization-based image resizing. In the past, a process of detecting precise locations of repeating patterns is required before the pattern removal step in resizing. However, it is difficult to find repeating patterns which are illuminated under different lighting conditions and viewed from different perspectives. To solve the problem, we first identify the regularity unit of repeating patterns by statistics. Then we can use the regularity unit for shift-map optimization to obtain a better resized image. The experimental results show that our method is competitive with other well-known methods.

关键词： image resizing image summarization repeating pattern removal

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Motion de-blurring based on time-evolution of simultaneous nonlinear reaction-diffusion

Motion de-blurring based on time-evolution of simultaneous n...

引用

conference on visual communications and image processing 2004

作者： Saito, T Harada, H Komatsu, T Kanagawa Univ Dept Elect Elect & Informat Eng Yokohama Kanagawa Japan

ISBN: (纸本)0819452114

Previously we have presented a method for selective image sharpness enhancement. Our method is based on the simultaneous nonlinear reaction-diffusion time-evolution equipped with a nonlinear diffusion term, a reaction term and an isotropic peaking term, and it can sharpen only degraded edges blurred by several causes without increasing the visibility of nuisance factors such as random noise. This paper applies our simultaneous nonlinear reaction-diffusion method to removal of image blurs due to image-motion. The motion blur is not only shift-variant but also anisotropic. To adapt our simultaneous nonlinear reaction-diffusion method for motion de-blurring, we replace the isotropic Laplacian operator, included in the isotropic peaking term of our prototypal method, with the anisotropic operator considering the direction of the estimated image motion. Preliminarily experiments using artificially generated test images show that our method achieves excellent motion de-blurring.

关键词： nonlinear partial differential equation nonlinear algorithm iterative algorithm image enhancement de-blurring nonlinear diffusion reaction-diffusion motion estimation motion blur

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An Efficient Vision Transformer Model for PCB Component Classification 31

An Efficient Vision Transformer Model for PCB Component Clas...

引用

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

作者： Surmeli, Cagri Can Ekenel, Hazim Kemal Istanbul Tech Univ ASELSAN Inc Istanbul Turkiye Istanbul Tech Univ Istanbul Turkiye

ISBN: (纸本)9798350343557

Printed circuit board (PCB) assemblies in everyday electronic devices are mass-produced. As a result of this production volume, a fast way of visual inspection is necessary. An integral part of visual inspection systems is PCB component classification. In this paper, we have explored use of the Vision Transformer (ViT), which is a recent state-of-the-art image classification approach, for PCB component classification. We have employed several ViT models that are available in the literature and also proposed a new compact, efficient, and high performing ViT model, named as ViT-Mini. We have conducted extensive experiments on the FICS-PCB dataset in order to comparatively evaluate the ViT models' performance. The highest achieved accuracy is 99.46% for capacitor and resistor classification and 96.52% for classification of capacitor, resistor, inductor, transistor, diode, and IC. The proposed compact model's performance is comparable with the ones obtained with larger models, which indicates its suitability for real-time applications.

关键词： PCB Components image Classification Vision Transformers

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Segmentation in the loop: An iterative, object based algorithm for motion estimation

Segmentation in the loop: An iterative, object based algorit...

引用

conference on visual communications and image processing 2004

作者： Blume, H von Livonius, J Noll, TG Univ Technol RWTH Aachen Chair Elect Engn & Comp Syst Aachen Germany

ISBN: (纸本)0819452114

Motion estimation algorithms are a key component for multimedia systems and optimization of these algorithms is still a topic of current research. Promising approaches try to integrate into the motion estimation process besides pure grey level similarities further types of information, contained in the image. Due to the moderate quality of this additional information the integration has to be performed rather conservatively in order to reduce the risk of an even dramatic degradation of the vector field quality in some cases. Up to now there is no robust algorithm available, which yields a noticeable improvement for all types of motion and image scenes, without causing a loss of quality in critical situations. Within the scope of this contribution the application of high performance segmentation for the enhancement of motion vector fields is analyzed. Starting from these results a new iterative concept for object based motion estimation is developed, which combines the results of a classic motion estimation with the information of image segmentation and features a high robustness against segmentation errors. The results of this new algorithm are analyzed on the basis of different objective evaluation criterions and compared to classic motion estimation algorithms.

关键词： motion estimation block matching motion vector image segmentation object based algorithms rainfalling-watershed image format conversion

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Color image enhancement and evaluation algorithm based on human visual system

Color image enhancement and evaluation algorithm based on hu...

引用

IEEE International conference on Acoustics, Speech, and Signal processing

作者： Huang, KQ Wang, Q Wu, ZY Southeast Univ Dept Radio Engn Nanjing 210096 Peoples R China

We propose a novel color image enhancement method, Human visual system Controlled Color image Enhancement and Evaluation (HCCIEE) algorithm, and applied to color image by considering natural image quality metrics. This HCCIEE algorithm is based on multiscale representation of pattern, luminance and color processing in the human visual system. Experiments illustrated the HCCIEE algorithm can produce distinguished details while avoids artifacts, which often occur in conventional multiscale enhancement methods, as well as the production of images that appear as similar as possible to the viewer's perception of actual scenes.

关键词： image enhancement

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Low Light RAW image Enhancement Using Paired Fast Fourier Convolution and Transformer

Low Light RAW Image Enhancement Using Paired Fast Fourier Co...

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

作者： Zhang, Yichi Liu, Hengyu Ding, Dandan Ma, Zhan Hangzhou Normal Univ Sch Informat Sci & Technol Hangzhou Peoples R China Nanjing Univ Sch Elect Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9781665475921

Compared to RGB images non-linearly mapped from RAW data through the image Signal Processor (ISP), RAW data are linear to scene radiance and contain more native information, which is better to be modeled in many vision tasks. This work proposes to enhance low-light images in the RAW domain via a cross-scale framework using paired Fast Fourier Convolution (FFC) and Transformer, driving the network to characterize images effectively. The entire framework has three scales to abstract low-level, mid-level, and high-level representations of input images. We embed paired FFC and Transformer in each scale to attain spatial-spectral information extraction and aggregation. Specifically, by transforming features from the spatial domain into the spectral domain with FFC, pixel correlations can be effectively exploited locally and globally, generating representative features for the input image. Immediately, the Transformer using multi-head self-attention mechanism is applied to aggregate and embed important features. Experimental results demonstrate that our method significantly outperforms state-of-the-art low-light enhancement works in both full reference assessment metrics, including PSNR, MPSNR, and SSIM, and no-reference metrics, such as NIMA. Meanwhile, the perceptual quality of the proposed method is more visually pleasing than that of other methods.

关键词： Computational photography low-light transformer fast Fourier convolution

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DISTINGUISHING COMPUTER-GENERATED imageS FROM PHOTOGRAPHIC imageS: A TEXTURE-AWARE DEEP LEARNING-BASED METHOD

DISTINGUISHING COMPUTER-GENERATED IMAGES FROM PHOTOGRAPHIC I...

引用

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

作者： Zhang, Zicheng Sun, Wei Min, Xiongkuo Wang, Tao Lu, Wei Zhai, Guangtao Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China

ISBN: (纸本)9781665475921

With the rapid development of computer graphics and generative models, computers are capable of generating images containing non-existent objects and scenes. Moreover, the computer-generated (CG) images may be indistinguishable from photographic (PG) images due to the strong representation ability of neural network and huge advancement of 3D rendering technologies. The abuse of such CG images may bring potential risks for personal property and social stability. Therefore, in this paper, we propose a dual-stream neural network to extract features enhanced by texture information to deal with the CG and PG image classification task. First, the input images are first converted to texture maps using the rotation-invariant uniform local binary patterns. Then we employ an attention-based texture-aware feature enhancement module to fuse the features extracted from each stage of the dual-stream neural network. Finally, the features are pooled and regressed into the predicted results by fully connected layers. The experimental results show that the proposed method achieves the best performance among all three popular CG and PG classification databases. The ablation study and cross-database validation experiments further confirm the effectiveness and generalization ability of the proposed algorithm.

关键词： Computer-generated photographic image classification dual-stream neural network texture map

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A novel stereo image coding algorithm based on delaunay triangulation mesh

A novel stereo image coding algorithm based on delaunay tria...

引用

conference on visual communications and image processing 2004

作者： Han, JG Lu, ZY Xidian Univ Sch Telecommun Engn ISN Natl Key Lab Shaanxi 710071 Xian Peoples R China

ISBN: (纸本)0819452114

Stereo image compression is of growing interest because of new display technologies and the needs of telepresence systems. A variety of algorithms have appeared in the literature that make use of the framework of block-based disparity estimation and disparity-compensated residual coding. which is similar to the monoscopic image framework. So that it has several drawbacks, for example, blocking artifacts. In this paper, a novel adaptive DT mesh based stereoscopic image coding algorithm is proposed. The algorithm makes use of adaptive DT mesh to estimate disparity vectors, and EZDCT based residual image coding. The algorithm is performed in three steps: adaptive DT description for the reference image. disparity, vector estimation based mesh and simple occluded regions detection, and disparity vector and residual image coding. Much of this work concentrates on improving the veracity of disparity estimation using DT mesh model and encoding the residual image appropriately. Simulation results show that the proposed scheme achieves higher veracity of disparity estimation at least 10%, as compared to conventional algorithms. And compared with conventional compression algorithms, the algorithm improves average PSNR about 1 db. Especially at low bit rates, this algorithm achieves better perceptual quality of decoded image. as compared to a block-based coding scheme.

关键词： stereo image coding DT mesh disparity estimation residual image coding

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Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification

Seq-Masks: Bridging the gap between appearance and gait mode...

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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： Chang, Zhigang Yang, Zhao Chen, Yongbiao Zhou, Qin Zheng, Shibao Shanghai Jiao Tong Univ Inst Image Proc & Network Engn Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Biomed Engn Shanghai Peoples R China Shanghai Jiao Tong Univ Shanghai Key Lab Scalable Comp & Syst Shanghai Peoples R China

ISBN: (纸本)9781728185514

Video-based person re-identification (Re-ID) aims to match person images in video sequences captured by disjoint surveillance cameras. Traditional video-based person Re-ID methods focus on exploring appearance information, thus, vulnerable against illumination changes, scene noises, camera parameters, and especially clothes/carrying variations. Gait recognition provides an implicit biometric solution to alleviate the above headache. Nonetheless, it experiences severe performance degeneration as camera view varies. In an attempt to address these problems, in this paper, we propose a framework that utilizes the sequence masks (SeqMasks) in the video to integrate appearance information and gait modeling in a close fashion. Specifically, to sufficiently validate the effectiveness of our method, we build a novel dataset named MaskMARS based on MARS. Comprehensive experiments on our proposed large wild video Re-ID dataset MaskMARS evidenced our extraordinary performance and generalization capability. Validations on the gait recognition metric CASIA-B dataset further demonstrated the capability of our hybrid model. Our codes and dataset MaskMARS will be open-sourced as a strong baseline.

关键词： Multi-modal Fusion Video-based Person Re-ID Gait Recognition appearance model

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Human visual quality image/video compression techniques based on integer wavelet packet transform and SPIHT, and theirs application to mobile communications

Human visual quality image/video compression techniques base...

引用

conference on visual Information processing XIII

作者： Asdornwised, W Jitapunkul, S Chulalongkorn Univ Dept Elect Engn Digital Signal Proc Res Lab Bangkok 10330 Thailand

ISBN: (纸本)0819453617

In this paper, we present an efficient compression technique that is suitable for image/video communications over wireless (mobile) channel. Our technique uses basic directional difference operators to estimate corresponding detail subband images/videos from their approximation subband images/videos. We empirically found that the detail subband images/videos can be well approximated by the estimate subband images/videos. In this work, image and video are first decomposed using integer wavelet packet transform. Having established that detail subband images/videos can be estimated from the approximation subbands, the information needed to send over the wireless channel is only the most important subband images/videos, where we selected them via best basis selection algorithm. Next, after best basis selection, the selected subband components are encoded using either SPIHT (JPEG) for image or 3-D SPIHT for video and then the encoded data are sent over the wireless channel. The advantages of our algorithms are two folds. First, most of the computation used in our technique is performed in integer for the purpose of coding speed improvement. Second, the computation of our algorithm either SPIHT (JPEG) or 3-D SPIHT is reduced from its original computation by an order of magnitude. The reason is that in our algorithm either SPIHT (JPEG) or 3-D SPIHT is performed only on the set of important components (two or a few subband images/videos) instead of the whole image/video. Finally, we show that our proposed algorithm using SPIHT (3-D SPIHT) are better than pure JPEG (MPEG-2) both in terms of human visual image quality and computation complexity.

关键词： image compression Wavelets visualization image analysis Mobile communications Video compression 3D image processing Wavelet transforms 3D video compression visual compression

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