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

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A learning-based visual saliency fusion model for High Dynamic Range video (LBVS-HDR)

A learning-based visual saliency fusion model for High Dynam...

引用

European Signal processing conference (EUSIPCO)

作者： Amin Banitalebi-Dehkordi Yuanyuan Dong Mahsa T. Pourazad Panos Nasiopoulos ECE Department and ICICS at the University of British Columbia Vancouver BC Canada ICICS at the University of British Columbia & TELUS Communications Incorporation Canada

Saliency prediction for Standard Dynamic Range (SDR) videos has been well explored in the last decade. However, limited studies are available on High Dynamic Range (HDR) visual Attention Models (VAMs). Considering that the characteristic of HDR content in terms of dynamic range and color gamut is quite different than those of SDR content, it is essential to identify the importance of different saliency attributes of HDR videos for designing a VAM and understand how to combine these features. To this end we propose a learning-based visual saliency fusion method for HDR content (LVBS-HDR) to combine various visual saliency features. In our approach various conspicuity maps are extracted from HDR data, and then for fusing conspicuity maps, a Random Forests algorithm is used to train a model based on the collected data from an eye-tracking experiment. Performance evaluations demonstrate the superiority of the proposed fusion method against other existing fusion methods.

关键词： visualization Feature extraction image color analysis Training Databases Dynamic range Radio frequency

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Mathematical analysis of colon glands for cancer diagnosis

Mathematical analysis of colon glands for cancer diagnosis

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IEEE Signal processing and communications Applications (SIU)

作者： Celal Cigir Cenk Sokmensuer Cigdem Gunduz-Demir Bilgisayar Muhendisligi Bolumu Bilkent Universitesi Ankara Turkey Patoloji Anabilim Dalı Hacettepe Tıp Fakültesi Ankara Turkey

Neoplastic diseases including cancer cause organizational changes in tissues. Histopathological examination, which is routinely used for the diagnosis and grading of these diseases, relies on pathologists to identify such tissue changes under a microscope. However, as this examination mainly relies on the visual interpretation of pathologists, it may lead to a considerable amount of subjectivity. To reduce the subjectivity level, it is proposed to use computational methods that provide objective measures. These methods quantify the tissue changes associated with disease by defining features on tissue images. In this paper, colon glands are mathematically analyzed making use of different feature extraction approaches. In this analysis, morphological, intensity-based, and textural features are investigated and glands are classified using these features. Working on the images of 108 colon tissues of 36 patients, our experiments demonstrate that this classification leads to promising results for differentiating normal glands from the cancerous ones.

关键词： Cancer Mathematical analysis Colon Glands Diseases Microscopy Feature extraction image texture analysis

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Trajectories adaptive prediction based on image processing cerebellar model for ocular-motor systems in robotic heads

Trajectories adaptive prediction based on image processing c...

引用

IEEE International conference on Systems, Man and Cybernetics

作者： J.L. Pedreno-Molina A. Guerrero-Gonzalez F. Garcia-Cordova J. Lopez-Coronado Dept. of Information Technologies and Communications Politechnical University of Cartagena Cartagena SPAIN

In this work, a neural controller for delay compensation in image samples detected by an active vision system of robotic heads, in ocular tracking tasks is presented. This control architecture based on CMAC (cerebellar model articulation controller) model has the capacity of learning favored trajectories with less prediction error. This property is very important in robotic tasks of controlling the grasping or assembling of objects by a robotic arm. The main advantage of this cerebellar model is that the output is evaluated by means of a small number of memory cells that implies a high answer speed. Indeed, this visual robotic control avoids (as does the human system) the need to know the kinematics of the process. This prediction module has been integrated in an architecture of visual-motor coordination based on VAM (vector associative maps) models.

关键词： Trajectory image processing Robot kinematics Predictive models Robotic assembly Control systems Robot control Delay Machine vision Robot vision systems

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Energy-Efficient Video Streaming: A Study on Bit Depth and Color Subsampling

Energy-Efficient Video Streaming: A Study on Bit Depth and C...

引用

IEEE visual communications and image processing (VCIP)

作者： Hadi Amirpour Lingfeng Qu Jong Hwan Ko Cosmin Stejerean Christian Timmerer Christian Doppler Laboratory ATHENA Alpen-Adria-Universitat Klagenfurt Austria Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China Department of Electrical and Computer Engineering Sungkyunkwan University South Korea Meta Platforms Inc. Menlo Park USA

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

As video dimensions – including resolution, frame rate, and bit depth – increase, a larger bitrate is required to maintain a higher Quality of Experience (QoE). While videos are often optimized for resolution and frame rate to improve compression and energy efficiency, the impact of color space is often overlooked. Larger color spaces are essential for avoiding color banding and delivering High Dynamic Range (HDR) content with richer, more accurate colors, although this comes at the cost of higher processing energy. This paper investigates the effects of bit depth and color subsampling on video compression efficiency and energy consumption. By analyzing different bit depths and subsampling schemes, we aim to determine optimized settings that balance compression efficiency with energy consumption, ultimately contributing to more sustainable and high-quality video delivery. We evaluate both encoding and decoding energy consumption and assess the quality of videos using various metrics including PSNR, VMAF, ColorVideoVDP, and CAMBI. Our findings offer valuable insights for video codec developers and content providers aiming to improve the performance and environmental footprint of their video streaming services.

关键词： Energy consumption image coding image color analysis Energy resolution Bit rate Color Streaming media Energy efficiency Decoding Quality of experience

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The restoration of degraded old motion pictures

The restoration of degraded old motion pictures

引用

National conference on Radio Science (NSRC)

作者： M.M. Hadhoud M.I.M. Dessouky A.M. Abbas Department of electronics and communications Faculty of Electronic Engineering-Menouf Menoufia University Menouf Egypt

Due to bad storage and repeated projection, movies suffer from many degradations, such as blotches, sparkle, noise or missing data in different parts. This paper examines these problems and the use of some image restoration techniques, in conjunction with motion estimation techniques widely used in video coding, to restore these pictures. The three-step method of block matching is used for motion estimation. An algorithm based on motion estimation and applying the concepts of the temporal 3D median filter is used for restoration. The results of this method show visual improvement and high reduction of the blotches, sparkles and missing data. Using other image enhancement techniques, further improvement can be obtained.

关键词： Degradation Motion pictures image restoration image storage Motion estimation image sequences Filters image enhancement image processing Material storage

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Segmentation of histopathological images with Convolutional Neural Networks using Fourier features

Segmentation of histopathological images with Convolutional ...

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IEEE Signal processing and communications Applications (SIU)

作者： Nuh Hatipoğlu Gökhan Bilgin Bilgisayar Teknolojileri Bölümü Trakya Üniversitesi Edirne Türkiye Bilgisayar Mühendisliği Bölümü Yıldız Teknik Üniversitesi İstanbul Türkiye

The study aims to boost the success of the segmentation results by evaluating spatial relations in the segmentation of histopathalogical images. In the first step Fourier features are extracted from RGB color space of digital histopathalogical images. Training data sets are formed by selecting equal number of different cellular and extra-cellular structures in spatial domain from the images. Classification models of each training data set is obtained by utilizing Convolutional Neural Network (CNN), Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN) methods. visual and numerical outputs which are obtained from supervised training methods are presented for comparison purpose in the experimental results section.

关键词： Neural networks image segmentation Convolution Breast cancer Support vector machines MATLAB

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Physically-based painting style 3D image synthesis using GPU

Physically-based painting style 3D image synthesis using GPU

引用

2008 5th International conference on visual Information Engineering (VIE 2008)

作者： Tianding Chen Institute of Communications and Information Technology Zhejiang Gongshang University Hangzhou China

Realistic objects simulation is important in visual reality and its performance is impacted by physical shape computation. Due to fast development and robust programmability of graphics hardware recently, much research takes advantage of GPU (Graphics processing Unit) computation to accelerate simulations in virtual environment. This paper presents painting style synthesis that fully simulates image behaviors and synthesizes Chinese painting images on the programmable graphics hardware. Also, the physically-based approaches can provide impressive simulation results, emulate deformable objects just like the ones in real world. Nevertheless the computation involves several physical principles and requires large amount of computation resources. As a result, real time simulation is hard to achieve. Therefore, the ability to provide a deformable object simulation in painting style synthesis interactively or even in real-time is what we concern with. Furthermore, we propose two methods to accelerate ink simulation. Both methods are implemented using special functionalities on the modern graphics hardware. As result, our speedup implementation several times faster than original one.

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An Interactive image Retrieval Framework for Biomedical Articles Based on visual Region-of- Interest (ROI) Identification and Classification

An Interactive Image Retrieval Framework for Biomedical Arti...

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IEEE International conference on Healthcare Informatics, Imaging and Systems Biology (HISB)

作者： Mahmudur Rahman Daekeun You Matthew S. Simpson Sameer K. Antani Dina Demner-Fushman George R. Thoma Lister Hill National Center for Biomedical Communications U.S. National Library of Medicine Bethesda MD USA

This paper presents an interactive biomedical image retrieval system based on automatic visual region-of-interest (ROI) extraction and classification into visual concepts. In biomedical articles, authors often use annotation markers such as arrows, letters or symbols overlaid on figures and illustrations in the articles to highlight ROIs. These annotations are then referenced and correlated with concepts in the caption text or figure citations in the article text. This association creates a bridge between the visual characteristics of important regions within an image and their semantic interpretation. Our proposed method at first localizes and recognizes the annotations by utilizing a combination of rule-based and statistical image processing techniques. Identifying these assists in extracting ROIs that are likely to be highly relevant to the discussion in the article text. The image regions are then annotated for classification using biomedical concepts obtained from a glossary of imaging terms. Similar automatic ROI extraction can be applied to query images, or user may interactively mark an ROI. As a result of our method, visual characteristics of the ROIs can be mapped to text concepts and then used to search image captions. In addition, the system can toggle the search process from purely visual to a textual one (cross-modal) or integrate both visual and textual search in a single process (multi-modal) based on utilizing user feedback. The hypothesis, that such approaches would improve biomedical image retrieval, is validated through experiments on a biomedical article dataset of thoracic CT scans from the collection of imageCLEF'2010 medical retrieval track.

关键词： Biomedical imaging visualization Feature extraction Computed tomography Terminology Ontologies

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A study on Generative Adversarial Text to image Synthesis

A study on Generative Adversarial Text to Image Synthesis

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Electrical, Computer, communications and Mechatronics Engineering (ICECCME), International conference on

作者： Marjana Tahmid Samiul Alam Kalim Akram Kazi Muhammad Asif Ashrafi Dept. of CSE East Delta University Chittagong Bangladesh Dept. of EEE East Delta University Chittagong Bangladesh Dept. of CSE Ulm University Ulm Germany

image captioning is one of the most prevalent and difficult challenges in Natural Language processing and Computer Vision: given an image, a written description of the image must be developed. The counterpart of the text to image problem is text to image synthesis, which involves creating a picture from a written description. These challenges approximate language translation challenges from a high-level perspective. images and text are two separate "languages" to convey related information, just like equivalent semantics might be represented in two different languages. This is undoubtedly beneficial, however existing AI systems are a long way from achieving this. Strong neural network topologies, such GANs (Generative Adversarial Networks), have been found to provide effective outcomes in recent years. There are, however, some text to image synthesis algorithms that use GAN (Generative Adversarial Network) that attempt to directly map words and characters to image pixels utilizing image synthesis and natural language synthesis approaches. To reconcile these advancements in text as well as image modeling and successfully translate visual representations from characters to pixels, we design an innovative deep architecture and GAN formulation in this study. Here, the demonstration of our model has been done by generating plausible images of birds and flowers from detailed text descriptions.

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Interactive object segmentation using kernel density estimation based graph cuts

Interactive object segmentation using kernel density estimat...

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International conference on Wireless communications and Signal processing (WCSP)

作者： Zhongmin Han Baoyan Ding Zhi Liu Liquan Shen Zhaoyang Zhang School of Communication and Information Engineering Shanghai University Shanghai China Key Laboratory of Advanced Display and System Application Ministry of Education Shanghai China

This paper proposes an efficient and flexible interactive object segmentation approach using kernel density estimation based graph cuts. First, the user draws scribbles to roughly mark the interested object and background, respectively, and the likelihood of object versus background is evaluated for each pixel using nonparametric kernel density estimation. Then pixels are globally classified into object and background using graph cuts, which uses likelihood as data cost and gradient information to generate a spatial varying smoothness cost. If the user is not satisfied with the initially segmented object, the user is allowed to mark these undesirable regions by drawing additional scribbles. A local region for refinement is then adaptively determined, and pixel reclassification is performed to extract a more accurate object boundary. Experimental results on a variety of images demonstrate that interested objects with good visual quality can be extracted with less user interaction and a timely response.

关键词： Object segmentation Kernel image segmentation Humans Iterative algorithms Data mining Displays Pixel Cost function Parametric statistics

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