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International conference on communications and Signal processing

作者： Srividhya Sridhar Gnanou Florence Sudha Department of ECE Pondicherry Engineering College Puducherry India

ISBN: (数字)9781728149882

ISBN: (纸本)9781728149899

Friendly Progressive visual Secret Sharing (FPVSS) shares the secret image using meaningful shares to n users such that k(k ≤ n) or more than k users can reconstruct the secret image progressively without computations. Existing FPVSS have the problems such as residual trace of cover image, poor quality of meaningful shares and reconstructed image. Hence this paper implements FPVSS using essential shares to overcome the problems of existing work. In addition to that, the proposed scheme can also be used in hierarchy secret sharing. The simulation result shows the effectiveness of proposed scheme.

关键词： image reconstruction visualization Encryption Decoding Stacking Simulation

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Texture-Aware Network for Enhancing Inner Smoke Representation in visual Smoke Density Estimation

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IET Computer Vision 2025年第1期19卷

作者： Xia, Xue Peng, Yajing Li, Zichen Shi, Jinting Fang, Yuming School of Computing and Artificial Intelligence Jiangxi University of Finance and Economics Nanchang China Jiangxi Provincial Key Laboratory of Multimedia Intelligent Processing Nanchang China School of Vocational Education and Technology Jiangxi Agricultural University Nanchang China

Smoke often appears before visible flames in the early stages of fire disasters, making accurate pixel-wise detection essential for fire alarms. Although existing segmentation models effectively identify smoke pixels, they generally treat all pixels within a smoke region as having the same prior probability. This assumption of rigidity, common in natural object segmentation, fails to account for the inherent variability within smoke. We argue that pixels within smoke exhibit a probabilistic relationship with both smoke and background, necessitating density estimation to enhance the representation of internal structures within the smoke. To this end, we propose enhancements across the entire network. First, we improve the backbone by adaptively integrating scene information into texture features through separate paths, enabling smoke-tailored feature representation for further exploit. Second, we introduce a texture-aware head with long convolutional kernels to integrate both global and orientation-specific information, enhancing representation for intricate smoke structure. Third, we develop a dual-task decoder for simultaneous density and location recovery, with the frequency-domain alignment in the final stage to preserve internal smoke details. Extensive experiments on synthetic and real smoke datasets demonstrate the effectiveness of our approach. Specifically, comparisons with 17 models show the superiority of our method, with mean IoU improvements of 4.88%, 2.63%, and 3.17% on three test sets. (The code will be available on https://***/xia-xx-cv/TANet_smoke). © 2025 The Author(s). IET Computer Vision published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： image segmentation

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Frequency-domain analysis based exploitation of color channels for color image demosaicking 34

Frequency-domain analysis based exploitation of color channe...

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34th IEEE International conference on visual communications and image processing, VCIP 2019

作者： Jaiswal, Sunil Prasad Jakhetiya, Vinit Gui, Ke Guntuku, Sharath C. Singla, Ashutosh IIT Jammu India Beijing University of Technology China University of Pennsylvania United States TU Ilmenau Germany

ISBN: (纸本)9781728137230

Color-difference interpolation (CDI) has been a widely used technique for various color demosaicking methods. CDI-based methods perform interpolation in the color-difference domain assuming that the color-difference signal is a low-pass signal. Recently, a residual interpolation (RI) algorithm, which conducts interpolation in the residual domain, has been developed, and it assumes that the residual domain is flatter or smoother than the channel-difference domain. In this paper, we comprehensively show a frequency domain analysis of these assumptions and observe that it is image dependent and creates artifacts in the interpolated image. With this view, we propose an algorithm that uses the inter-color correlation as well as the residual smoothness among the different channel much better than the existing algorithms. Experimental results emphasize that the proposed algorithm atribute better performances the existing algorithms in terms of both visual and objective quality. © 2019 IEEE.

关键词： Interpolation

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UGNet: Underexposed images Enhancement Network based on Global Illumination Estimation

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

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IEEE visual communications and image processing (VCIP)

作者： Yuan Fang Wenzhe Zhu Qing Zhu School of Software Engineering Beijing University of Technology Beijing China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

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： Lighting image color analysis Convolution image enhancement Estimation Training Task analysis

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Accommodation and Vergence Responses to Electronic Holographic Displays Compared with Those to Stereoscopic Displays

Accommodation and Vergence Responses to Electronic Holograph...

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conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： Haruki Mizushina Ippei Negishi Junya Nakamura Yasuhiro Takaki Hiroshi Ando Shinobu Masaki Tokushima University Tokushima Japan Kanazawa Institute of Technology Ishikawa Japan Tokyo University of Agriculture and Technology Tokyo Japan National Institute of Information and Communications Technology Osaka Japan Advanced Telecommunications Research Institute International Kyoto Japan

ISBN: (纸本)9781728164021

Electronic holography is an ideal 3D display technique to ameliorate vergence-accommodation conflict, which is a possible cause of visual fatigue and discomfort from viewing conventional stereoscopic 3D displays. Previous studies have measured accommodative and vergence responses to holographic images and real objects, and reported that they are in good agreement. To demonstrate the effectiveness of electronic holography as a solution of vergence-accommodation conflict caused by viewing conventional stereoscopic 3D displays, we measured accommodative and vergence responses to reconstructed images of holograms and two-view stereoscopic images. We also measured responses to real objects located at various distances as a baseline condition. The results indicate that the accommodative response to the electro-holographic display changes with the vergence response in a similar manner, as is the case with real objects as compared to conventional two-view stereo display. This suggests that the holographic display technology is a promising candidate for resolving the vergence-accommodation conflict.

关键词： visualization Three-dimensional displays image resolution Stereo image processing Industry applications Virtual reality Human factors

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A Weighted Mean Absolute Error Metric for image Quality Assessment

A Weighted Mean Absolute Error Metric for Image Quality Asse...

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IEEE visual communications and image processing (VCIP)

作者： Sihan Hao Sumei Li Tianjin University Tianjin P.R. China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

Pixel-wise image quality assessment (IQA) algorithms, such as mean square error (MSE), mean absolute error (MAE) and peak signal-to-noise ratio (PSNR) correlate well with perceptual quality when dealing with images sharing the same distortion type but not well when processing images in different distortion types, which is inconsistent with human visual system (HVS). Although a large number of metrics based on image error has been proposed, there are still difficulties and limitations. To solve this problem, a full reference image quality assessment (FR-IQA) method based on MAE is proposed in this paper. The metric divides the image error (difference between distorted image and reference image) map into smooth region and texture-edge region, calculates their mean values respectively, and then gives them different weights considering the masking effect. The key innovation of this paper is to propose a distortion significance measurement, which is a visual quality coefficient that can effectively indicate the influence of different distortion types on perceptual quality and unify them with HVS. The segmented image error maps are weighted by the distortion significance coefficient. The experimental results on four largest benchmark databases show that the most of the distortions are successfully evaluated and the results are consistent with HVS.

关键词： Distortion image quality Databases Mathematical model image edge detection Quality assessment PSNR

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Extending CCSDS 123.0-B-1 for Lossless 4D image Compression

Extending CCSDS 123.0-B-1 for Lossless 4D Image Compression

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IEEE visual communications and image processing (VCIP)

作者： Panpan Zhang Xiuheng Wang Tiande Gao Zhenfu Feng Jie Chen Center of Intelligent Acoustics and Immersive Communications School of Marine Science and Technology Northwestern Polytechnical University China School of Electronic Engineering Xi’an University of Posts & Telecommunications China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

A 4-dimensional (4D) image can be viewed as a stack of volumetric images over channels of observation depth or temporal frames. This data contains rich information at the cost of high demands for storage and transmission resources due to its large volume. In this paper, we present a lossless 4D image compression algorithm by extending CCSDS-123.0-B-1 standard. Instead of separately compressing the volumetric image at each channel of 4D images, the proposed algorithm efficiently exploits redundancy across the fourth dimension of data. Experiments conducted on two types of 4D images demonstrate the effectiveness of the proposed lossless compression method.

关键词： image coding Three-dimensional displays Standards Fish Metadata Redundancy Hyperspectral imaging

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Stereo image Quality Assessment Considering the Asymmetry of Statistical Information in Early visual Pathway

Stereo Image Quality Assessment Considering the Asymmetry of...

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IEEE visual communications and image processing (VCIP)

作者： Yongli Chang Sumei Li Li Ma Jie Jin School of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

The design of stereo image quality assessment (SIQA) methods cannot be well based on the biological theory of human vision, so the performance of many SIQA methods cannot achieve good consistency with the subjective perception. The research on the visual system tends to the dorsal and ventral pathways, which ignores the information asymmetry in the early visual pathways. It is worth noting that the ON and OFF receptive fields in retinal ganglion cells (RGCs) respond asymmetrically to the statistical features of images. Inspired by this, we propose a SIQA method based on monocular and binocular visual features, which takes into account the asymmetry of local contrast bright and dark features in early visual pathways. First, this paper extracts the response maps of ON and OFF cell in RGCs to left and right views respectively. And then the different information fusion modes of visual cortex are used to fuse the response maps information of left and right views. Final, monocular and binocular features were extracted and sent to support vector regression (SVR) for quality regression. Experimental results show that the proposed method is superior to several mainstream SIQA metrics on two publicly available databases.

关键词： visualization Feature extraction Distortion Information filters image quality Retina Brain modeling

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CBIR Systems: Techniques and Challenges

CBIR Systems: Techniques and Challenges

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International conference on communications and Signal processing

作者： Niveditha Arunkumar A Ranjith Ram Department of Electronics and Communication Government College of Engineering Kannur Kerala India faculty of Department of Electronics and Communication Government College of Engineering Kannur Kerala India

ISBN: (数字)9781728149882

ISBN: (纸本)9781728149899

The vigorous growth and continual intelligibility of visual information on the cyberspace have led to the richness of research projects in image search and retrieval. With the lack of concern on the visual contents of an image, the text based search techniques for image retrieval often suffers variability between the text words and visual content. Hence Content Based image Retrieval (CBIR) has achieved a great appeal as it models the perceptual content of an image to identify similar relevant images. This paper aims at discussing the evolution of retrieval techniques, paying particular attention on development, merits, demerits and challenges of the image retrieval. It focuses on reviewing the already existing techniques and its related issues. The enormous development of image data necessitates the need for the expansion of research and helps in the progress of efficient and accurate image retrieval. Also, CBIR maintains a sustained growth in the research field.

关键词： Feature extraction image color analysis image segmentation image retrieval visualization Semantics

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Extreme image coding via multiscale autoencoders with generative adversarial optimization 34

Extreme image coding via multiscale autoencoders with genera...

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34th IEEE International conference on visual communications and image processing, VCIP 2019

作者： Huang, Chao Liu, Haojie Chen, Tong Shen, Qiu Ma, Zhan Nanjing University Vision Lab China

ISBN: (纸本)9781728137230

We propose a MultiScale AutoEncoder (MSAE) based extreme image coding/compression framework to offer visually pleasing reconstruction at a very low bitrate. Our method leverages the "priors" at different resolution scale to improve the compression efficiency, and also employs the generative adversarial network (GAN) with multiscale discriminators to perform the end-To-end trainable rate-distortion optimization. We compare the perceptual quality of our reconstructions with traditional compression algorithms using High-Efficiency Video Coding (HEVC) based Intra Profile and JPEG2000 on the public Cityscapes, ADE20K and Kodak datasets, demonstrating the significant subjective quality improvement. However, objective measurements, such as PSNR, SSIM, etc, are often deteriorated by applying the generative adversarial optimization. © 2019 IEEE.

关键词： image coding

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