A fast method for image noise estimation using Laplacian operator and adaptive edge detection

2008 ◽  
Author(s):  
Shen-Chuan Tai ◽  
Shih-Ming Yang
Keyword(s):  
Edge Detection ◽  
Image Noise ◽  
Noise Estimation ◽  
Laplacian Operator ◽  
Fast Method

Digital Image Noise Estimation Using DWT Coefficients

2021 ◽  
Vol 30 ◽  
pp. 1962-1972
Author(s):  
Varad A. Pimpalkhute ◽  
Rutvik Page ◽  
Ashwin Kothari ◽  
Kishor M. Bhurchandi ◽  
Vipin Milind Kamble
Keyword(s):  
Digital Image ◽  
Image Noise ◽  
Noise Estimation

scholarly journals Using Improved Edge Detection Method to Detect Mining-Induced Ground Fissures Identified by Unmanned Aerial Vehicle Remote Sensing

2021 ◽  
Vol 13 (18) ◽  
pp. 3652
Author(s):  
Duo Xu ◽  
Yixin Zhao ◽  
Yaodong Jiang ◽  
Cun Zhang ◽  
Bo Sun ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Edge Detection ◽  
Unmanned Aerial Vehicle ◽  
Field Experiments ◽  
High Efficiency ◽  
Detection Method ◽  
Laplacian Operator ◽  
Ground Fissures ◽  
Aerial Vehicle ◽  
Edge Detection Method

Information on the ground fissures induced by coal mining is important to the safety of coal mine production and the management of environment in the mining area. In order to identify these fissures timely and accurately, a new method was proposed in the present paper, which is based on an unmanned aerial vehicle (UAV) equipped with a visible light camera and an infrared camera. According to such equipment, edge detection technology was used to detect mining-induced ground fissures. Field experiments show high efficiency of the UAV in monitoring the mining-induced ground fissures. Furthermore, a reasonable time period between 3:00 a.m. and 5:00 a.m. under the studied conditions helps UAV infrared remote sensing identify fissures preferably. The Roberts operator, Sobel operator, Prewitt operator, Canny operator and Laplacian operator were tested to detect the fissures in the visible image, infrared image and fused image. An improved edge detection method was proposed which based on the Laplacian of Gaussian, Canny and mathematical morphology operators. The peak signal-to-noise rate, effective edge rate, Pratt’s figure of merit and F-measure indicated that the proposed method was superior to the other methods. In addition, the fissures in infrared images at different times can be accurately detected by the proposed method except at 7:00 a.m., 1:00 p.m. and 3:00 p.m.

scholarly journals Fast horizon detection in maritime images using region-of-interest

2018 ◽  
Vol 14 (7) ◽  
pp. 155014771879075 ◽  
Author(s):  
Chi Yoon Jeong ◽  
Hyun S Yang ◽  
KyeongDeok Moon
Keyword(s):  
Edge Detection ◽  
State Of The Art ◽  
Region Of Interest ◽  
Least Square ◽  
Fast Method ◽  
Multi Scale ◽  
Art Methods ◽  
Horizon Line ◽  
Horizon Detection ◽  
Interest Detection

In this article, we propose a fast method for detecting the horizon line in maritime scenarios by combining a multi-scale approach and region-of-interest detection. Recently, several methods that adopt a multi-scale approach have been proposed, because edge detection at a single is insufficient to detect all edges of various sizes. However, these methods suffer from high processing times, requiring tens of seconds to complete horizon detection. Moreover, the resolution of images captured from cameras mounted on vessels is increasing, which reduces processing speed. Using the region-of-interest is an efficient way of reducing the amount of processing information required. Thus, we explore a way to efficiently use the region-of-interest for horizon detection. The proposed method first detects the region-of-interest using a property of maritime scenes and then multi-scale edge detection is performed for edge extraction at each scale. The results are then combined to produce a single edge map. Then, Hough transform and a least-square method are sequentially used to estimate the horizon line accurately. We compared the performance of the proposed method with state-of-the-art methods using two publicly available databases, namely, Singapore Marine Dataset and buoy dataset. Experimental results show that the proposed method for region-of-interest detection reduces the processing time of horizon detection, and the accuracy with which the proposed method can identify the horizon is superior to that of state-of-the-art methods.

An image-noise estimation approach using singular value decomposition

2016 ◽  
Author(s):  
Mingfu He ◽  
Mingzhe Liu ◽  
Chengqiang Zhao ◽  
Jianbo Yang ◽  
Helen Zhou
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Image Noise ◽  
Noise Estimation ◽  
Value Decomposition

scholarly journals Efficient image noise estimation based on skewness invariance and adaptive noise injection

2020 ◽  
Vol 14 (7) ◽  
pp. 1393-1401
Author(s):  
Ben Ma ◽  
Jincao Yao ◽  
Yanfen Le ◽  
Chuan Qin ◽  
Heng Yao
Keyword(s):  
Image Noise ◽  
Noise Estimation ◽  
Noise Injection ◽  
Adaptive Noise

scholarly journals Image Characteristic Extraction of Ice-Covered Outdoor Insulator for Monitoring Icing Degree

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5305
Author(s):  
Yong Liu ◽  
Qiran Li ◽  
Masoud Farzaneh ◽  
B. X. Du
Keyword(s):  
Power Systems ◽  
Edge Detection ◽  
High Speed ◽  
Video Camera ◽  
Detection Algorithm ◽  
Image Noise ◽  
Accident Risk ◽  
Ice Accretion ◽  
Structural Problems ◽  
Growth Method

Serious ice accretion will cause structural problems and ice flashover accidents, which result in outdoor insulator string operating problems in winter conditions. Previous investigations have revealed that the thicker and longer insulators are covered with ice, the icing degree becomes worse and icing accident probability increases. Therefore, an image processing method was proposed to extract the characteristics of the icicle length and Rg (ratio of the air gap length to the insulator length) of ice-covered insulators for monitoring the operation of iced outdoor insulator strings. The tests were conducted at the artificial climate room of CIGELE Laboratories recommended by IEEE Standard 1783/2009. The surface phenomena of the insulator during the ice accretion process were recorded by using a high-speed video camera. In the view of the ice in the background of the picture of fuzzy features and high image noise, a direct equalization algorithm is used to enhance the grayscale iced image contrast. The median filtering method is conducted for reducing image noise and sharpening the image edge. The maximum entropy threshold segmentation algorithm is put forward to extract the insulators and its surface ice from the background. Then, the modified Canny operator edge detection algorithm is selected to trace the boundaries of objects through the extraction of information about attributes of the endpoints of edges. After we obtained the improved Canny edge detection image for both of the ice-covered insulators and non-iced insulators, the icing thickness can be obtained by calculating the difference between the edge of the non-iced insulators image and the edge of the iced insulator image. Besides, in order to identify the icing degree of the insulators more accurately, this paper determines the location of icicles by using the region growth method. After that, the icicle length and Rg can be obtained to monitor the icing degree of the insulator. It will be helpful to improve the ability to judge the accident risk of insulators in power systems.

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