scholarly journals CNN-Based Suppression of False Contour and Color Distortion in Bit-Depth Enhancement

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 416
Author(s):  
Changmeng Peng ◽  
Luting Cai ◽  
Xiaoyang Huang ◽  
Zhizhong Fu ◽  
Jin Xu ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Large Volume ◽  
State Of The Art ◽  
Visual Quality ◽  
Cost Effective ◽  
Visual Data ◽  
Color Distortion ◽  
Critical Issues ◽  
Enhancement Method ◽  
Depth Enhancement

It is a challenge to transmit and store the massive visual data generated in the Visual Internet of Things (VIoT), so the compression of the visual data is of great significance to VIoT. Compressing bit-depth of images is very cost-effective to reduce the large volume of visual data. However, compressing the bit-depth will introduce false contour, and color distortion would occur in the reconstructed image. False contour and color distortion suppression become critical issues of the bit-depth enhancement in VIoT. To solve these problems, a Bit-depth Enhancement method with AUTO-encoder-like structure (BE-AUTO) is proposed in this paper. Based on the convolution-combined-with-deconvolution codec and global skip of BE-AUTO, this method can effectively suppress false contour and color distortion, thus achieving the state-of-the-art objective metric and visual quality in the reconstructed images, making it more suitable for bit-depth enhancement in VIoT.

scholarly journals IRC-GAN: Introspective Recurrent Convolutional GAN for Text-to-video Generation

2019 ◽  
Author(s):  
Kangle Deng ◽  
Tianyi Fei ◽  
Xin Huang ◽  
Yuxin Peng
Keyword(s):  
Mutual Information ◽  
State Of The Art ◽  
Visual Quality ◽  
Semantic Distance ◽  
Experimental Results ◽  
Video Frame ◽  
Semantic Consistency ◽  
Critical Issues ◽  
Definition Of ◽  
The Given

Automatically generating videos according to the given text is a highly challenging task, where visual quality and semantic consistency with captions are two critical issues. In existing methods, when generating a specific frame, the information in those frames generated before is not fully exploited. And an effective way to measure the semantic accordance between videos and captions remains to be established. To address these issues, we present a novel Introspective Recurrent Convolutional GAN (IRC-GAN) approach. First, we propose a recurrent transconvolutional generator, where LSTM cells are integrated with 2D transconvolutional layers. As 2D transconvolutional layers put more emphasis on the details of each frame than 3D ones, our generator takes both the definition of each video frame and temporal coherence across the whole video into consideration, and thus can generate videos with better visual quality. Second, we propose mutual information introspection to semantically align the generated videos to text. Unlike other methods simply judging whether the video and the text match or not, we further take mutual information to concretely measure the semantic consistency. In this way,  our model is able to introspect the semantic distance between the generated video and the corresponding text, and try to minimize it to boost the semantic consistency.We conduct experiments on 3 datasets and compare with state-of-the-art methods. Experimental results demonstrate the effectiveness of our IRC-GAN to generate plausible videos from given text.

Detection of Malicious Spatial-Domain Steganography over Noisy Channels Using Convolutional Neural Networks

2020 ◽  
Vol 2020 (4) ◽  
pp. 76-1-76-7
Author(s):  
Swaroop Shankar Prasad ◽  
Ofer Hadar ◽  
Ilia Polian
Keyword(s):  
State Of The Art ◽  
Visual Quality ◽  
Channel Noise ◽  
Detection Accuracy ◽  
Noisy Channel ◽  
Noisy Channels ◽  
Reliable Transmission ◽  
Reliable Detection ◽  
Natural Noise ◽  
Will Force

Image steganography can have legitimate uses, for example, augmenting an image with a watermark for copyright reasons, but can also be utilized for malicious purposes. We investigate the detection of malicious steganography using neural networkbased classification when images are transmitted through a noisy channel. Noise makes detection harder because the classifier must not only detect perturbations in the image but also decide whether they are due to the malicious steganographic modifications or due to natural noise. Our results show that reliable detection is possible even for state-of-the-art steganographic algorithms that insert stego bits not affecting an image’s visual quality. The detection accuracy is high (above 85%) if the payload, or the amount of the steganographic content in an image, exceeds a certain threshold. At the same time, noise critically affects the steganographic information being transmitted, both through desynchronization (destruction of information which bits of the image contain steganographic information) and by flipping these bits themselves. This will force the adversary to use a redundant encoding with a substantial number of error-correction bits for reliable transmission, making detection feasible even for small payloads.

Underwater Image Enhancement Method Combining color and Luminance

2020 ◽  
Vol 13 ◽  
Author(s):  
ZHAO Baiting ◽  
WANG Feng ◽  
JIA Xiaofen ◽  
GUO Yongcun ◽  
WANG Chengjun
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Brightness Enhancement ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method ◽  
Frequency Components ◽  
Image Contour ◽  
Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

scholarly journals Underwater Image Enhancement Based on Local Contrast Correction and Multi-Scale Fusion

2021 ◽  
Vol 9 (2) ◽  
pp. 225
Author(s):  
Farong Gao ◽  
Kai Wang ◽  
Zhangyi Yang ◽  
Yejian Wang ◽  
Qizhong Zhang
Keyword(s):  
Image Enhancement ◽  
Local Contrast ◽  
Fusion Method ◽  
Formation Model ◽  
Low Contrast ◽  
White Balance ◽  
Multi Scale ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method

In this study, an underwater image enhancement method based on local contrast correction (LCC) and multi-scale fusion is proposed to resolve low contrast and color distortion of underwater images. First, the original image is compensated using the red channel, and the compensated image is processed with a white balance. Second, LCC and image sharpening are carried out to generate two different image versions. Finally, the local contrast corrected images are fused with sharpened images by the multi-scale fusion method. The results show that the proposed method can be applied to water degradation images in different environments without resorting to an image formation model. It can effectively solve color distortion, low contrast, and unobvious details of underwater images.

scholarly journals Disentangled generative adversarial network for low-dose CT

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Wenchao Du ◽  
Hu Chen ◽  
Hongyu Yang ◽  
Yi Zhang
Keyword(s):  
Network Architecture ◽  
Low Dose ◽  
Noise Suppression ◽  
State Of The Art ◽  
Visual Quality ◽  
Ct Images ◽  
Generative Adversarial Network ◽  
Low Dose Ct ◽  
Adversarial Network ◽  
Suppression Method

AbstractGenerative adversarial network (GAN) has been applied for low-dose CT images to predict normal-dose CT images. However, the undesired artifacts and details bring uncertainty to the clinical diagnosis. In order to improve the visual quality while suppressing the noise, in this paper, we mainly studied the two key components of deep learning based low-dose CT (LDCT) restoration models—network architecture and adversarial loss, and proposed a disentangled noise suppression method based on GAN (DNSGAN) for LDCT. Specifically, a generator network, which contains the noise suppression and structure recovery modules, is proposed. Furthermore, a multi-scaled relativistic adversarial loss is introduced to preserve the finer structures of generated images. Experiments on simulated and real LDCT datasets show that the proposed method can effectively remove noise while recovering finer details and provide better visual perception than other state-of-the-art methods.

scholarly journals ART-UP: A Novel Method for Generating Scanning-Robust Aesthetic QR Codes

2021 ◽  
Vol 17 (1) ◽  
pp. 1-23
Author(s):  
Mingliang Xu ◽  
Qingfeng Li ◽  
Jianwei Niu ◽  
Hao Su ◽  
Xiting Liu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Visual Quality ◽  
Qr Code ◽  
Quick Response ◽  
Estimation Model ◽  
Qr Codes ◽  
Excellent Performance ◽  
Novel Method ◽  
Coarse To Fine

Quick response (QR) codes are usually scanned in different environments, so they must be robust to variations in illumination, scale, coverage, and camera angles. Aesthetic QR codes improve the visual quality, but subtle changes in their appearance may cause scanning failure. In this article, a new method to generate scanning-robust aesthetic QR codes is proposed, which is based on a module-based scanning probability estimation model that can effectively balance the tradeoff between visual quality and scanning robustness. Our method locally adjusts the luminance of each module by estimating the probability of successful sampling. The approach adopts the hierarchical, coarse-to-fine strategy to enhance the visual quality of aesthetic QR codes, which sequentially generate the following three codes: a binary aesthetic QR code, a grayscale aesthetic QR code, and the final color aesthetic QR code. Our approach also can be used to create QR codes with different visual styles by adjusting some initialization parameters. User surveys and decoding experiments were adopted for evaluating our method compared with state-of-the-art algorithms, which indicates that the proposed approach has excellent performance in terms of both visual quality and scanning robustness.

scholarly journals Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Real Life ◽  
Computation Time ◽  
Cost Effective ◽  
Battery Life ◽  
Cross Layer ◽  
Security Level ◽  
Cost Of Energy ◽  
Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

scholarly journals Removal of heavy metal ions from wastewater: a comprehensive and critical review

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Naef A. A. Qasem ◽  
Ramy H. Mohammed ◽  
Dahiru U. Lawal
Keyword(s):  
Heavy Metal ◽  
Metal Ions ◽  
Large Volume ◽  
Heavy Metal Ions ◽  
Membrane Separation ◽  
Cost Effective ◽  
Operating Conditions ◽  
Future Research ◽  
Sludge Formation ◽  
Metals Removal

AbstractRemoval of heavy metal ions from wastewater is of prime importance for a clean environment and human health. Different reported methods were devoted to heavy metal ions removal from various wastewater sources. These methods could be classified into adsorption-, membrane-, chemical-, electric-, and photocatalytic-based treatments. This paper comprehensively and critically reviews and discusses these methods in terms of used agents/adsorbents, removal efficiency, operating conditions, and the pros and cons of each method. Besides, the key findings of the previous studies reported in the literature are summarized. Generally, it is noticed that most of the recent studies have focused on adsorption techniques. The major obstacles of the adsorption methods are the ability to remove different ion types concurrently, high retention time, and cycling stability of adsorbents. Even though the chemical and membrane methods are practical, the large-volume sludge formation and post-treatment requirements are vital issues that need to be solved for chemical techniques. Fouling and scaling inhibition could lead to further improvement in membrane separation. However, pre-treatment and periodic cleaning of membranes incur additional costs. Electrical-based methods were also reported to be efficient; however, industrial-scale separation is needed in addition to tackling the issue of large-volume sludge formation. Electric- and photocatalytic-based methods are still less mature. More attention should be drawn to using real wastewaters rather than synthetic ones when investigating heavy metals removal. Future research studies should focus on eco-friendly, cost-effective, and sustainable materials and methods.

Ultrasonic Cavitation Based Processing of Metal Matrix Nanocomposites: An Overview

2014 ◽  
Vol 1042 ◽  
pp. 58-64 ◽  
Author(s):  
Santanu Sardar ◽  
Santanu Kumar Karmakar ◽  
Debdulal Das
Keyword(s):  
Mass Production ◽  
Metal Matrix ◽  
Cost Effective ◽  
Ultrasonic Cavitation ◽  
Basic Principles ◽  
Metal Matrix Nanocomposites ◽  
Microstructural Parameters ◽  
Structural Applications ◽  
Critical Issues ◽  
Matrix Nanocomposites

Metal matrix nanocomposites (MMNCs) have emerged as an important class of materials for structural applications specifically in the automobile and aerospace sectors; however, development of cost effective mass production technique of MMNCs with requisite operational and geometrical flexibilities is still a great challenge. Focused research in the last decade has highlighted that ultrasonic cavitation based processing is the most promising method for manufacturing of MMNCs with nearly uniform distribution of nanoparticles, having added advantage of being a liquid-phase route. This article presents an overview on the basic principles and recent advances in the ultrasonic cavitation based processing of MMNCs with a particular emphasis on identifying relationships amongst processing variables, microstructural parameters and mechanical properties. Critical issues of MMNCs fabrication are discussed.

IN MINIMAL ACCESS SURGERY

1996 ◽  
Vol 17 (12) ◽  
pp. 441-447
Author(s):  
Thom E Lobe
Keyword(s):  
Medical Care ◽  
Pediatric Patient ◽  
Endoscopic Surgery ◽  
State Of The Art ◽  
Outpatient Surgery ◽  
Cost Effective ◽  
Surgical Instruments ◽  
Short Stay ◽  
Minimal Access ◽  
Access Surgery

The pediatrician must be cognizant of the extensive applications of endoscopic surgery in the pediatric patient. The ability to provide either outpatient surgery or short-stay surgery appears to be cost-effective and appropriate state-of-the-art medical care. As the array of surgical instruments continues to evolve, new and innovative endoscopic procedures will become increasingly available.

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