scholarly journals Terahertz Image Enhancing Based on the Physical Model and Multiscale Retinex Algorithm

2021 ◽  
Author(s):  
qi mao ◽  
yunlong zhu ◽  
jingbo liu ◽  
cixing lv ◽  
yao lu ◽  
...  
Keyword(s):  
Physical Model ◽  
Dynamic Range ◽  
Atmospheric Scattering ◽  
Retinex Algorithm ◽  
Enhancement Method ◽  
Image Enhancing ◽  
Thz Absorption ◽  
Image Details ◽  
Degradation Problem

Abstract To settle the THz image degradation problem, we propose an effective enhancement method based on the physical model and multiscale retinex (MSR) algorithm. The overall enhancing process involves two parts: reconstruction and enhancement. Firstly, the original THz images are reconstructed by a mathematical model, which is built and considered the THz absorption variate and Gaussian distribution of the beam. Then, the original images are processed by the proposed algorithm, which is combined the atmospheric scattering model and optimized MSR algorithm. The proposed algorithm not only recover the image scene radiance and remove haze, but also can make a compromise of the dynamic range of grayscale and edge enhancement of image. Results on a variety of THz images demonstrate our method can effectively improve the quality of THz images and retain sufficient image details.

Single Image Dehazing by Predicting Atmospheric Scattering Parameters

2020 ◽  
Vol 2020 (1) ◽  
pp. 74-77
Author(s):  
Simone Bianco ◽  
Luigi Celona ◽  
Flavio Piccoli
Keyword(s):  
Reference Image ◽  
Single Image ◽  
Scattering Parameters ◽  
Image Dehazing ◽  
Atmospheric Scattering ◽  
Local Structures ◽  
Full Reference ◽  
Reconstruction Quality ◽  
Single Image Dehazing

In this work we propose a method for single image dehazing that exploits a physical model to recover the haze-free image by estimating the atmospheric scattering parameters. Cycle consistency is used to further improve the reconstruction quality of local structures and objects in the scene as well. Experimental results on four real and synthetic hazy image datasets show the effectiveness of the proposed method in terms of two commonly used full-reference image quality metrics.

Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

2017 ◽  
Vol 7 (8) ◽  
pp. 56
Author(s):  
Ashish Dwivedi ◽  
Nirupma Tiwari
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Human Perception ◽  
Histogram Equalization ◽  
Wavelet Shrinkage ◽  
Visual Appearance ◽  
Enhancement Method ◽  
Fuzzy Histogram ◽  
Rgb Image

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

Radiometric resolution and dynamic range of aerial and space images, obtained for monitoring and mapping purposes

2020 ◽  
Vol 964 (10) ◽  
pp. 40-48
Author(s):  
I.A. Anikeeva
Keyword(s):  
Dynamic Range ◽  
Numerical Estimation ◽  
Space Images

The dynamic range and radiometric resolution are among the most important indicators of aerial and space images’ fine quality. Gradation properties are of particular importance for aerial and space images, obtained for monitoring and mapping purposes, because the completeness and quality of the information on the earth’s surface objects depend on them, the accuracy of brightness features reproduction of earth’s surface objects. The author discusses various approaches to defining the concepts of dynamic range and radiometric resolution; the most proper definitions of these terms are given in the context of estimating the image’s gradation properties. The expediency of separating the concepts of nominal, actual and useful (effective) radiometric resolution is shown; their definitions are given. Methods of dynamic range and radio-metric resolution numerical estimation based on a histogram are shown. Absolute and relative indicators are considered. The advantages of using relative indicators are shown. Examples of the dynamic range and radiometric resolution evaluation are given basing upon the images obtained by ‘‘Canopus-B’’ spacecraft.

scholarly journals Deterioration Causes Evaluation of Third Generation Cellular LTE Services for Moving Unmanned Terrestrial and Aerial Systems

2018 ◽  
Vol 14 (2) ◽  
pp. 141-148
Author(s):  
Deniss Brodņevs ◽  
Aleksandrs Kutins
Keyword(s):  
Data Transfer ◽  
Angular Position ◽  
Operating Conditions ◽  
Service Performance ◽  
Negative Effects ◽  
Lte Networks ◽  
Wireless Signal ◽  
Aerial Systems ◽  
Degradation Problem

AbstractWell-deployed cellular networks offer a cheap wireless solution for the control channel deployment of Remote-Control Vehicles (RCV) and Unmanned Aerial Vehicles (UAV). However, a cellular data transfer service performance is affected by a different kind of User Equipment (UE) mobility. Operating conditions of UAV imply working at different altitudes, variable velocities with accelerations/decelerations and rapidly changed antennas angular position, which lead the wireless signal to be prone to negative effects. Available field measurement studies are not sufficient to provide excessive information on degradation problem causes for UEs moving along a complex trajectory. This paper presents an evaluation of the service quality of live operational 3G and LTE networks for both ground moving and flying UE. It has been found that antennas angular position variations in 3D (for example, during UAV manoeuvers) increase data transfer latency and jitter. Moreover, this effect in conjunction with higher interference at high altitudes may partially or fully block the data transfer service. This paper has been prepared to draw attention to the problem that makes the cellular data transfer service unusable for highly-manoeuvrable UAVs.

A Method to Enhance the Fog Image Based on Dark Object Subtraction

2014 ◽  
Vol 543-547 ◽  
pp. 2484-2487
Author(s):  
Jing Zhang ◽  
Wei Dong ◽  
Jian Xin Wang ◽  
Xu Ning Liu
Keyword(s):  
Dynamic Range ◽  
Color Space ◽  
Threshold Value ◽  
Entropy Method ◽  
Image Contrast ◽  
Dark Object ◽  
Image Contrast Enhancement ◽  
Degraded Image ◽  
Enhancement Method ◽  
Rgb Color Space

Aiming at the problem of poor image contrast and low visibility, a single image contrast enhancement method is put forward in this paper. The method is based on Dark-object subtraction technique, translating the fog degraded image from RGB color space to YIQ color space, and taking out the Y component. Then using the maximum entropy method to get the threshold value of image segmentation, we can put different portion of the image according to the different formula for image restoration. The processed image must be converted from YIQ color space to RGB color space In the back of the steps. Finally, the image needs a linear dynamic range adjustment to enhance the contrast and brightness. Experiments show that the method can effectively remove haze effect on the image. The dehazing effect of the processed image is obvious. The image becomes clear and bright, and the details is outstanding, which is convenient for observation and analysis.

Perceptual Quality Assessment of Low-light Image Enhancement

2021 ◽  
Vol 17 (4) ◽  
pp. 1-24
Author(s):  
Guangtao Zhai ◽  
Wei Sun ◽  
Xiongkuo Min ◽  
Jiantao Zhou
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Enhancement ◽  
Dynamic Range ◽  
State Of The Art ◽  
Perceptual Quality ◽  
Low Light ◽  
Light Image ◽  
Light Enhancement

Low-light image enhancement algorithms (LIEA) can light up images captured in dark or back-lighting conditions. However, LIEA may introduce various distortions such as structure damage, color shift, and noise into the enhanced images. Despite various LIEAs proposed in the literature, few efforts have been made to study the quality evaluation of low-light enhancement. In this article, we make one of the first attempts to investigate the quality assessment problem of low-light image enhancement. To facilitate the study of objective image quality assessment (IQA), we first build a large-scale low-light image enhancement quality (LIEQ) database. The LIEQ database includes 1,000 light-enhanced images, which are generated from 100 low-light images using 10 LIEAs. Rather than evaluating the quality of light-enhanced images directly, which is more difficult, we propose to use the multi-exposure fused (MEF) image and stack-based high dynamic range (HDR) image as a reference and evaluate the quality of low-light enhancement following a full-reference (FR) quality assessment routine. We observe that distortions introduced in low-light enhancement are significantly different from distortions considered in traditional image IQA databases that are well-studied, and the current state-of-the-art FR IQA models are also not suitable for evaluating their quality. Therefore, we propose a new FR low-light image enhancement quality assessment (LIEQA) index by evaluating the image quality from four aspects: luminance enhancement, color rendition, noise evaluation, and structure preserving, which have captured the most key aspects of low-light enhancement. Experimental results on the LIEQ database show that the proposed LIEQA index outperforms the state-of-the-art FR IQA models. LIEQA can act as an evaluator for various low-light enhancement algorithms and systems. To the best of our knowledge, this article is the first of its kind comprehensive low-light image enhancement quality assessment study.

The functioning investigation of the network semi-active damping system for wheeled vehicle

2021 ◽  
pp. 21-28
Keyword(s):  
System Identification ◽  
Physical Model ◽  
Network Model ◽  
Active Damping ◽  
Central Processor ◽  
Active System ◽  
Physical Network ◽  
Wheeled Vehicle ◽  
Road Profile

The tasks related to the construction of a united semi-active system for damping vibrations of the supporting platform (chassis) of a wheeled vehicle (WV), taking into account the real road profile were considered. The influence estimation of the network on the functioning resulting quality of the entire united damping system is carried out. The modeling of the network united of the model of one wheelset, the possible law of control of the suspension, the central processor and the physical model of the CAN network by using the National Instruments equipment is performed. The results of the experiments, both purely mathematical and with a physical network model, showed the performance of the proposed solutions. Keywords CAN-tire; semi-active suspension system; identification; modeling

Medical Image Enhancement Using Edge Information-Based Methods

2017 ◽  
pp. 123-148
Author(s):  
S. Anand
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Hyperbolic Function ◽  
Edge Information ◽  
X Ray ◽  
Enhancement Method ◽  
Chest X Ray ◽  
Medical Image Enhancement

Medical image enhancement improves the quality and facilitates diagnosis. This chapter investigates three methods of medical image enhancement by exploiting useful edge information. Since edges have higher perceptual importance, the edge information based enhancement process is always of interest. But determination of edge information is not an easy job. The edge information is obtained from various approaches such as differential hyperbolic function, Haar filters and morphological functions. The effectively determined edge information is used for enhancement process. The retinal image enhancement method given in this chapter improves the visual quality of the vessels in the optic region. X-ray image enhancement method presented here is to increase the visibility of the bones. These algorithms are used to enhance the computer tomography, chest x-ray, retinal, and mammogram images. These images are obtained from standard datasets and experimented. The performance of these enhancement methods are quantitatively evaluated.

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