• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.535-544
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• 2020

In synthetic aperture radar (SAR) based ship detection application, false alarms frequently occur due to various noises caused by the radar imaging process. Among them, radio frequency interference (RFI) and azimuth smearing produce substantial false alarms; the latter also yields longer length estimation of ships than the true length. These two noises are prominent at cross-polarization and relatively weak at co-polarization. However, in general, the cross-polarization data are suitable for ship detection, because the radar backscatter from background sea surface is much less in comparison with the co-polarization backscatter, i.e., higher ship-sea image contrast. In order to improve the ship detection accuracy further, the RFI and azimuth smearing need to be mitigated. In the present letter, Sentinel-1 VV- and VH-polarization intensity data are used to show a novel technique of removing these noises. In this method, median image intensities of noises and background sea surface are calculated to yield arithmetic tendency. A band-math formula is then designed to replace the intensities of noise pixels in VH-polarization with adjusted VV-polarization intensity pixels that are less affected by the noises. To verify the proposed method, the adaptive threshold method (ATM) with a sliding window was used for ship detection, and the results showed that the 74.39% of RFI false alarms are removed and 92.27% false alarms of azimuth smearing are removed.

• Geophysics and Geophysical Exploration
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• v.15 no.4
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• pp.199-208
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• 2012

High-amplitude swell noises (HASN) are very difficult to eliminate from the marine seismic data. In this paper, we applied F-X filter and median filter in order to suppress HASN. Test data have been acquired on the northern offshore of the South Shetland Islands in December, 2010. Parts of data have been contaminated by HASN caused by bad weather during the cruise. We applied F-X filter and median filter to test data with HASN. After F-X filtering, most of non-coherent noises and small-amplitude swell noises are eliminated effectively but HASN are still remained significantly. With median filter, HASN was suppressed better than F-X filter, however some of non-coherent noises are still remains. We applied a cascade of two filters and results show HASN and non-coherent noises are suppressed effectively. After the cascade of two filtering, it is possible to define reflection layers clearly on the velocity spectrum and to produce better stacked section with a good signal-to-noise ratio.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.970-976
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• 2012

In this paper, a single LRF has been used to produce a 3D map for the mobile robot navigation. The 2D laser scanners are used for mobile robots navigation, where the laser scanner is applied to detect a certain level of area by the straight beam. Therefore it is limited to the usages of 2D obstacle detection and avoidance. In this research, it is designed to complement a mobile robot system to move up and down a single LRF along the yaw axis. During the up and down motion, the 2D data are stacked and manipulated to build a 3D map. Often a single LRF data are mixed with Gaussian and impulse noises. The impulse noises are removed out by the hybrid median filter designed in this research. The 2D data which are improved by deleting the impulse noises are layered to build the 3D map. Removing impulse noises while preserving the boundary is a main advantages of the hybrid median filter which has been used widely to improve the quality of images. The effectiveness of this hybrid median filter for rejecting the impulse noises has been verified through the real experiments. The performance of the hybrid median filter is evaluated in terms of PSNR (Peak Signal to Noise Ratio) and the processing time.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.37-45
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• 2020

The development process of deep learning is an iterative task that requires a lot of manual work. Among the steps in the development process, pre-processing of learning data is a very costly task, and is a step that significantly affects the learning results. In the early days of AI's algorithm research, learning data in the form of public DB provided mainly by data scientists were used. The learning data collected in the real environment is mostly the operational data of the sensors and inevitably contains various noises. Accordingly, various data cleaning frameworks and methods for removing noises have been studied. In this paper, we proposed a method for detecting and removing noises from time-series data, such as sensor data, that can occur in the IoT environment. In this method, the linear regression method is used so that the system repeatedly finds noises and provides data that can replace them to clean the learning data. In order to verify the effectiveness of the proposed method, a simulation method was proposed, and a method of determining factors for obtaining optimal cleaning results was proposed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.49-53
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• 2008

This study deals a way to reduce the transformer noises. The first step is to identify the source of the transformer noises. The second step is obtaining the vibration characteristics of transformer; its natural frequencies and mode shapes. Based on these information, an method to reduce the vibration of transformer can be found. The cause of transformer noises is mainly due to the magnetostrictive vibration of a core which is made of ferromagnetic substances. It is well known that the magnetostrictive vibration of a core is unavoidable, and a way to reduce the transformer noise by structural design is needed. It requires understanding the vibration characteristics. The natural frequencies and the mode shapes of transformer are analyzed by performing the modal testing.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.58-60
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• 2008

In this paper, In this investigation we measured and evaluated effects to residential area as result of noises caused by building vibration when the turbine of hydro-electric power station runs, and establishes the best plan of soundproof for that area. Furthermore, we analyzed differences between estimated noises and actual noises and its causes before constructing the soundproofing panels so that it helps to start building the soundproofing panels and similar constructions in the future.

• Journal of Oral Medicine and Pain
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• v.21 no.1
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• pp.103-113
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• 1996

The author examined the clinical signs and symptoms , routine radiographs, laboratory test and bone scan in 73 subjects with TMJ disorders and studied the responses of clinical test on patients, the distribution of signs and symptoms of joints, the simple uptake rate(SUR) of affected joints , the SUR of subclassified groups of TMJ disorders, active joints of subclassified groups of TMJ disorders and the SUR of joints with noises. The obtained results were as follows : 1. The percentage of joint pain on palpation, joint noises joint pain on function, mandibular dysfunction and active finding of bone scan in aptients with TMJ disorders were higher 2. The SUR was higher in joints affected by joint pain on function, joint pain on palpation, mandibular dysfunction and creptius. 3. The SUR of osteoarthrosis was the lowest. 4. The percentage of active joints were the highest in joints with discdisplacement without reduction, and followed by osteoarthritis, and disc displacement with reduction. 5. The SUR of TMJ showing joint noises only was lower.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.61-67
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• 1999

A laser Doppler vibrometer based on the laser heterodyne interferometry is employed to measure the vibration velocity of vibrating objects. In this paper, we propose a real time analog signal processor of a laser Doppler vibrometer to reduce the degradation of Doppler signals mainly caused by environmental noises. In the proposed real time signal processor of an laser Doppler vibrometer, a pre-processor and a logical motion direction detector are designed to reduce the detection errors of the object motion direction. Also, a noise detection and rejection circuit is designed to reject the unfiltered noises.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.109-111
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• 2002

Visual organs play an important role in human information recognition processes. If they are expressed in a way of digital information, it makes much bigger amount of visual information among any other information. For that reason, MPEG-2 has been taken use of to represent information compressing technology in multi-media. Although the imported data would basically contain noises, when original video images are encoded into MPET-2. Accordingly, we propose soft- $\alpha$ filter to improve image quality of digital image received from the actual image and to reduce noises from them. We also propose a method combining vertical/horizontal filter and soft- $\alpha$ filter on MPEG-2 video image. We can get two kinds of effects from the advantages of this kind of combination. Firstly, it will reduce processing time ducting horizontal and vetical filtering process. It will cover time for soft- $\alpha$ filter. Secondly, it will simplify the colors in horizontal and vertical filter. Therefore we can get clearer quality without noises from soft- $\alpha$ filter.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.4
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• pp.289-298
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• 2014

Pass-by noises of various trains were recorded by binaural recorder. The measured noises were evaluated using a sound pressure level and psychoacoustic metrics objectively. To analyze a binaural effect on annoyance that can be caused by train noise, auditory experiments were performed. Through the experiments, the annoyance differences between monaural and binaural train noises, the annoyance differences due to measurement angle and the annoyance differences due to kinds of train and measurement distance were determined. A correlation analysis was conducted to determine which index can affect the annoyance more strongly. As the result, a maximum rate of change of sharpness difference between left and right channels was proposed to predict the annoyance.