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IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Hanyu Li Peixian Zhuang Wang Wei Jingjing Li Nanjing University of Information Science and Technology Nanjing China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Clear and clean underwater images can provide valuable information, which are crucial for developing, exploring, and protecting the underwater resources. However, the raw underwater image seldom fulfills the requirements concerning the underwater research due to the serious image degradation. To enhance single underwater image, we propose an effective and new method combined on the dehazing and color correction algorithm. First, we obtain the dehazed image by a fusion dehazing method calculated on the difference between maximum green-blue dark channels and maximum red dark channel, and the top 0:1% bright pixels in green-blue dark channels. Second, we obtain the enhanced image via the color restoration method corresponding to the human visual system. Finally, we use an efficient and simple weight fusion strategy to incorporate the dehazed image and the enhanced image for yielding the final high quality underwater image. Subjective assessment demonstrates that our method can remove haze, correct color cast, improve image brightness, and preserve image naturalness. The enhanced results obtain the highest values in terms of entropy, average gradient, UCIQE, UIQM, and CCF, which is superior to several existing underwater enhancement methods. Moreover, our method can improve other degraded image quality, such as low-light image and haze image, and can benefit the application tests, such as key points matching and edge detection.

关键词： image color analysis Degradation image restoration image edge detection image quality Channel estimation image enhancement

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A Quantization Watermarking Scheme Based on Perceptual Invisibility Model

A Quantization Watermarking Scheme Based on Perceptual Invis...

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9th International conference on Signal processing(第九届国际信号处理学术会议)(ICSP'08)

作者： Chi-Pio Tou Chi-Man Pun Lin Dong Department of Computer and Information Science University of Macau

With the increasing researches in embedding watermarks in DWT domains,exploiting the HVS model while embedding have raised interests in the *** for embedding in low and/or high frequencies domains had been proposed in some literatures,but seldom of them take into account of the considerations of display visual resolution (dvr) as a *** this paper,we proposed a novel scheme which adapt the quantization modulation technique and employ the Watson's invisibility model as the quantization factor in modulation for governing the perceptual *** cover images has been used for *** of the watermarks can be 100％ detected without any attacks and under low pass filter *** for JPEG 50 quality compression,extraction rate can be higher than 99.5％.As the inadequate and/or insufficient of using PSNR to evaluate the perceptual quality of watermarked images,MSSIM will also be used for evaluation in our work.

关键词： Quantization Watermarking Discrete wavelet transforms Frequency domain analysis Displays Testing Low pass filters Transform coding image coding PSNR

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image Compressed Sensing Reconstruction via Deep image Prior with Feature Space and Texture Information 8th

Image Compressed Sensing Reconstruction via Deep Image Prior...

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8th International conference on Cognitive Systems and Information processing, ICCSIP 2023

作者： Peng, Zhao Jinchan, Wang Huanqing, Peng Fei, Xiang Liwen, Zhang College of Information Engineering Henan University of Science and Technology Luoyang471023 China

ISBN: (纸本)9789819980178

Deep learning has yielded remarkable achievements in compressed sensing image reconstruction in recent years. However, when the sampling rate is low, the reconstruction image is blurred and lacks texture details. In this paper, we design a dual-path compressed sensing reconstruction network based on image feature space information flow and texture information, which can solve the above problems to a certain extent. The feature space information flow path employs proximal gradient descent algorithms to map essential structural information from the pixel space to the feature space, effectively reducing data dimensionality and redundancy. On the other hand, after combining the attention mechanism, the texture information path restores the texture details of the image in the frequency domain, which can effectively enhance the quality and visual effects of the reconstruction image. During training, a unified loss function guides the alternating optimization of both paths. Evaluation of prominent benchmark datasets, including Set5, Set11, and BSD68, reveals that our proposed method outperforms traditional iterative approaches and existing deep learning-based methodologies in terms of both reconstructed image quality and network robustness under low sampling rates. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image reconstruction

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QEVC: Quality Enhancement-Oriented Video Coding

QEVC: Quality Enhancement-Oriented Video Coding

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International conference on Computers, communications, and Systems (ICCCS)

作者： Hao Li Weimin Lei Wei Zhang School of Computer Science and Engineering Northeastern University Shenyang P. R. China

ISBN: (数字)9781728161365

ISBN: (纸本)9781728161372

Quality enhancement (QE) is an important post-processing technology for high-resolution video services at low bit rates, which can effectively improve the quality of compressed video. The application of deep learning methods to the quality enhancement task has achieved great success in the past few years. However, the existing schemes are usually coding-independent, which still leaves room for further development of related technologies. Therefore, in this paper, we propose a quality enhancement-oriented video coding scheme. By analyzing the features of different video regions, a deep reinforcement learning model is used to determine the distortions of regions. Then during the video reconstruction, convolutional neural network (CNN)-based quality enhancement networks with different scales are selected to improve the video quality according to the distortion of different regions. Experimental results show that the proposed scheme outperforms the HEVC anchor in case of bits saving, bits allocation, and shows good visual quality especially at low bit rates.

关键词： image coding Distortion Indexes Training Bit rate Task analysis Encoding

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Mean Shift Tracking Combining SIFT

Mean Shift Tracking Combining SIFT

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2008 9th International conference on Signal processing(ICSP’2008)

作者： Ai-hua Chen 1 2 Ming Zhu 1 Yan-hua Wang 1 2 Chen Xue 1 2 1.Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of sciences,Changchun 130033,P.R.China 2.Graduate School of the Chinese Academy of Sciences,Beijing,China

A novel visual tracking algorithm to cope with occlusion and scale variation is *** method combines mean shift and SIFT algorithm to track *** algorithm is invariant to rotation,translation and scale *** it is a timeconsuming *** wasting time is related to image *** the proposed algorithm first adopts mean shift to initially locate object position,then SIFT operator is used to detect features in object area and model area,lastly,the proposed method matches features in these two areas and calculates the relationship between them using affine *** to affine transform parameters,the state of object can be adjusted in *** order to reduce process time,an improved feature matching algorithm is proposed in this *** show that the proposed algorithm deals with occlusion successfully and can adjust object size in time.

关键词： Mean Shift Tracking Combining SIFT image

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FREQ-MIP-AA: Frequency Mip Representation for Anti-Aliasing Neural Radiance Fields

FREQ-MIP-AA: Frequency Mip Representation for Anti-Aliasing ...

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IEEE International conference on image processing

作者： Youngin Park Seungtae Nam Cheul-Hee Hahm Eunbyung Park Department of Digital Media and Communications Engineering Sungkyunkwan University Visual Display Division Samsung Electronics Department of Artificial Intelligence Sungkyunkwan University Department of Electrical and Computer Engineering Sungkyunkwan University

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Neural Radiance Fields (NeRF) have shown remarkable success in representing 3D scenes and generating novel views. However, they often struggle with aliasing artifacts, especially when rendering images from different camera distances from the training views. To address the issue, Mip-NeRF proposed using volumetric frustums to render a pixel and suggested integrated positional encoding (IPE). While effective, this approach requires long training times due to its reliance on MLP architecture. In this work, we propose a novel antialiasing technique that utilizes grid-based representations, usually showing significantly faster training time. In addition, we exploit frequency-domain representation to handle the aliasing problem inspired by the sampling theorem. The proposed method, FreqMipAA, utilizes scale-specific low-pass filtering (LPF) and learnable frequency masks. Scale-specific low-pass filters (LPF) prevent aliasing and prioritize important image details, and learnable masks effectively remove problematic high-frequency elements while retaining essential information. By employing a scale-specific LPF and trainable masks, FreqMipAA can effectively eliminate the aliasing factor while retaining important details. We validated the proposed technique by incorporating it into a widely used grid-based method. The experimental results have shown that the FreqMipAA effectively resolved the aliasing issues and achieved state-of-the-art results in the multi-scale Blender dataset. Our code is available at https://***/yi0109/FreqMipAA.

关键词： Training image coding Three-dimensional displays Codes Filtering Frequency-domain analysis Low-pass filters

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Four new adaptive systems for four medical applications — part 1

Four new adaptive systems for four medical applications — p...

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conference of the North American Fuzzy Information processing Society - NAFIPS

作者： M. Buscema Semeion Research Center of Science of Communications Rome Italy

In this work we will try to introduce to four complex Artificial Adaptive Systems, able to be applied directly to medical field with interesting results. Each of these Systems is not a simple algorithm, but a set of adaptive systems, able each time to cooperate and to compete to reach an optimal solution. The four artificial adaptive systems we present in this work are: 1. An auto-contractive map able to project a dataset into a weighted graph, whose connections show hidden non linear relations among data; 2. An active connection matrix, named J-Net, able to show in any kind of medical image features invisible to human eyes and to the other imaging filter and techniques; 3. A new methodology to read the semantic of a set of points distributed into a 2 or 3 dimensional space, named topological weighted centroid (TWC). This system should be able to approximate the origin point of epidemic and its trend, only starting from the distribution in the space of same cases; 4. A new system, named IFAST (implicit function as squashing time), dedicated to detect the invariants from a multi-sequence of signals along the time. IFAST show to be a suitable techniques to analyse the EEG of patients to understand the quality of their brain activity.

关键词： Adaptive systems Medical services Biomedical equipment Biomedical imaging Equations Humans Eyes Filters Electroencephalography Brain

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Genre Classification of Movie Trailers using Spectrogram Analysis and Machine Learning

Genre Classification of Movie Trailers using Spectrogram Ana...

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International Black Sea conference on communications and Networking (BlackSeaCom)

作者： Porawat Visutsak Fuangfar Pensiri Ponrudee Netisopakul Navapoom Punsathit Pongkorn Rojsuwan Maywadee Phuthong Worapol Khanthawat Wittawat Prommanee Kanthong Jearaphan Tawichai Saekua Tichaporn Anantaprueksa Napas Kavalee Naravitch Sukkokee Nanticha Kingket Prapassorn Teeravas Patchara Nimmonrat Patcharada Yungyuen Pattareeya Nurltes Ratchanon Wongpanti Sekson Hompangwhai Haritchaya Sutthikawee Apichai Siangchin Department of Computer and Information Science Faculty of Applied Science KMUTNB Bangkok Thailand Department of Computer Science and Information Faculty of Science at Sriracha Kasetsart University Chonburi Thailand Faculty of Information Technology KMITL Bangkok Thailand

ISBN: (数字)9798350351859

ISBN: (纸本)9798350351866

This study investigates the application of machine learning for movie trailer genre classification using spectrogram analysis. Spectrograms, visual representations of a signal's frequency content over time, are extracted from movie trailers. Convolutional Neural Networks (CNNs), known for their image recognition capabilities, are employed to analyze these spectrograms and identify patterns that distinguish between different genres. Our approach is compared to a Random Forest model for performance evaluation. The models are trained on a dataset of movie trailers categorized into five genres: action, romance, drama, comedy, and thriller. Librosa, a Python library, is utilized for audio pre-processing, while the overall training process is conducted within the Python environment. This paper explores the potential of machine learning in conjunction with spectrogram analysis for effective movie trailer genre classification.

关键词： Training Performance evaluation visualization Time-frequency analysis Humanities image recognition Motion pictures

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Transfer learning based multi-class malware classification using VGG16 feature extractor and SVM classifier

Transfer learning based multi-class malware classification u...

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International conference on communications and Signal processing

作者： Harman Saggu Er. Karandeep Singh T. N. Suresh Babu Department of Computer Science and Engineering Punjabi University Patiala India Department of Electronics and Communication Engineering Adhiparasakthi Engineering College Tamil Nadu India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

Malicious programs are becoming a severe problem in today’s internet-connected world. Several works have explored image analysis-based malware detection in recent years. The image analysis method converts the malicious code into gray-scale images, which enables the use of deep learning models in the domain of malware detection. This paper proposes a new architecture using a fine-tuned visual Geometry Group(VGG16) model with a support vector machine (SVM) classifier to achieve high-performance accuracy in detecting and classifying evolving malware. At first, the malicious code is represented in gray-scale images, which are further reshaped and resized to be fed into a fine-tuned VGG16 model as end-to-end feature extraction with the least dependence on human-crafted feature engineering. The extracted textural feature maps are further correlated to remove the highly correlated features before using them to train a support vector machine (SVM) classifier. The experiments are performed on public bench-marked MalImg datasets and actual malware samples. The VGG 16+ SVM model obtained 99.25% classification accuracy for the MalImg and 80.29% for real-world malware, which signifies that the model can detect real-world instances of malware. The proposed method outperforms similar existing works and is suitable for deployment in an IoT environment due to the least cost involved in feature engineering.

关键词： Support vector machines Geometry Deep learning visualization image analysis Costs Transfer learning

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Saturn's icy satellites investigated by Cassini-VIMS II. Results at the end of nominal mission

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ICARUS 2010年第2期206卷 507-523页

作者： Filacchione, G. Capaccioni, F. Clark, R. N. Cuzzi, J. N. Cruikshank, D. P. Coradini, A. Cerroni, P. Nicholson, P. D. McCord, T. B. Brown, R. H. Buratti, B. J. Tosi, F. Nelson, R. M. Jaumann, R. Stephan, K. Ist Astrofis Spaziale & Fis Cosm INAF IASF Area Ric Tor Vergata I-00133 Rome Italy US Geol Survey Fed Ctr Denver CO 80228 USA NASA Ames Res Ctr Moffett Field CA 94035 USA Ist Fis Spazio Interplanetario INAF Area Ric Tor Vergata I-00133 Rome Italy Cornell Univ Dept Astron Ithaca NY 14853 USA Bear Fight Ctr Winthrop WA 98862 USA Univ Arizona Lunar & Planetary Lab Tucson AZ 85721 USA Univ Arizona Steward Observ Tucson AZ 85721 USA CALTECH Jet Prop Lab Pasadena CA 91109 USA DLR Inst Planetary Explorat D-12489 Berlin Germany

We report the detailed analysis of the spectrophotometric properties of Saturn's icy satellites as derived by full-disk observations obtained by visual and infrared mapping spectrometer (VIMS) experiment aboard Cassini. In this paper, we have extended the coverage until the end of the Cassini's nominal mission (June 1st 2008), while a previous paper (Filacchione, G., and 28 colleagues [2007]. Icarus 186, 259290, hereby referred to as Paper I) reported the preliminary results of this study. During the four years of nominal mission, VIMS has observed the entire population of Saturn's icy satellites allowing us to make a comparative analysis of the VIS-NIR spectral properties of the major satellites (Mimas, Enceladus, Tethys, Dione, Rhea, Hyperion, Iapetus) and irregular moons (Atlas. Prometheus, Pandora, Janus, Epimetheus, Telesto, Calypso, Phoebe). The results we discuss here are derived from the entire dataset available at June 2008 which consists of 1417 full-disk observations acquired from a variety of distances and inclinations from the equatorial plane, with different phase angles and hemispheric coverage. The most important spectrophotometric indicators (as defined in Paper I: I/F continua at 0.55 mu m, 1.822 mu m and 3.547 mu m visible spectral slopes, water and carbon dioxide bands depths and positions) are calculated for each observation in order to investigate the disk-integrated composition of the satellites, the distribution of water ice respect to "contaminants" abundances and typical regolith grain properties. These quantities vary from the almost pure water ice surfaces of Enceladus and Calypso to the organic and carbon dioxide rich Hyperion, Iapetus and Phoebe. Janus visible colors are intermediate between these two classes having a slightly positive spectral slope. These results could help to decipher the origins and evolutionary history of the minor moons of the Saturn's system. We introduce a polar representation of the spectrophotometric parameter

关键词： Saturn, Satellites Spectroscopy Ices, IR spectroscopy Infrared observations image processing

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