• The Journal of Korea Robotics Society
• /
• v.18 no.3
• /
• pp.271-280
• /
• 2023

FMCW (Frequency Modulated Continuous Wave) radar system is widely used in autonomous driving and navigation applications due to its high detection capabilities independent of weather conditions and environments. However, radar signals can be easily contaminated by various noises such as speckle noise, receiver saturation, and multipath reflection, which can worsen sensing performance. To handle this problem, we propose a learning-free noise removal technique for radar to enhance detection performance. The proposed method leverages adaptive thresholding to remove speckle noise and receiver saturation, and wavelet transform to detect multipath reflection. After noise removal, the radar image is reconstructed with the geometric structure of the surrounding environments. We verify that our method effectively eliminated noise and can be applied to autonomous driving by improving the accuracy of odometry and place recognition.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.487-491
• /
• 2009

The inverse halftoning is processing to restore the image made binary to former step image. There are smoothing and gaussian filtering in the technique so far. However, there are still a lot of insufficient points in past inverse halftoning. The removal of the noise and the edge enhansment are closely related in inverse halftoning. It is difficult to do both the noise rednctiom and the edge enhansment in high accuracy at the same time in the technique so far. The technique that can achieve both the removal of the noise and the emphasis of Edge at the same time is expected as future tasks. Then, it was tried to apply the Kalmann filtering to inverse halftoning. In the actual experiment, the effectiveness of the application of the Kalmann filtering to inverse halftoning comparing it with the technique so far was shown.

• KIEE International Transaction on Systems and Control
• /
• v.2D no.2
• /
• pp.115-119
• /
• 2002

In this paper we present a generalized directional morphological filtering algorithm for the removal of impulse noise, which is based on a combination of impulse noise detection and a weighted rank-order morphological filtering technique. For salt (or pepper) noise suppression, the generalized directional opening (or closing) filtering of the input signal is selectively used. The detection of impulse noise can be done by the geometrical difference of opening and closing filtering. Simulations show that this new filter has better detail feature preservation with effective noise reduction compared to other nonlinear filtering techniques.

• Journal of information and communication convergence engineering
• /
• v.20 no.3
• /
• pp.195-203
• /
• 2022

Noise generated during image acquisition and transmission can negatively impact the results of image processing applications, and noise removal is typically a part of image preprocessing. Denoising techniques combined with nonlocal techniques have received significant attention in recent years, owing to the development of sophisticated hardware and image processing algorithms, much attention has been paid to; however, this approach is relatively poor for edge preservation of fine image details. To address this limitation, the current study combined a steering kernel technique with adaptive masks that can adjust the size according to the noise intensity of an image. The algorithm sets the steering weight based on a similarity comparison, allowing it to respond to edge components more effectively. The proposed algorithm was compared with existing denoising algorithms using quantitative evaluation and enlarged images. The proposed algorithm exhibited good general denoising performance and better performance in edge area processing than existing non-local techniques.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.51 no.3
• /
• pp.340-347
• /
• 2015

The Commission for Conservation of Antarctic Marine Living Resources (CCAMLR) is utilized to manage krill resources using acoustic data collection and a scientific observer program operating on the fishing boats. However, the acoustic data were contained seriously noise, example of background, spike, and intermittent noise, due to purpose of fish boats. In this study, the noise removal techniques were confirmed the potential of the acoustic data analysis. Acoustic system and frequency used in the survey were commercial echosounder (ES70, SIMRAD) and 200 kHz split beam transducer. Acoustic data were analyzed using Echoview software (Myriax), and general data analysis and new noise removal method was used. Although a variety of noise, most of the noises have been removed using the noise removal processing. We confirmed the possibility of analyzing the acoustic data obtained from fish boats. The results will be useful for analysis of the acoustic data acquired from krill fishing boats.

• International journal of advanced smart convergence
• /
• v.7 no.4
• /
• pp.169-173
• /
• 2018

Iris diagnosis based on the color and texture information is one of a novel approach which can represent the current state of a certain organ inside body or the health condition of a person. In analysis of the iris images, there are critical image artifacts which can prevent of use interpretation of the iris textures on images. Here, we developed the iris diagnosis system based on a hand-held typed imaging probe which consists of a single camera sensor module with 8M pixels, two pairs of 400~700 nm LED, and a guide beam. Two original images with different light noise pattern were successively acquired in turns, and the light noise-free image was finally reconstructed and demonstrated by the proposed artifact removal approach.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.8
• /
• pp.1436-1441
• /
• 2016

Currently, partial discharge diagnosis in the field of prevention applied technology and diagnostic equipment is a possible strong limit to remove the noise generated by external or internal I still have one unreliable diagnosis. This technology is the noise removal from signal the time lag analysis algorithms technique is applied by a fundamental. Increasing the reliability in terms of technology spectrum frequence of analysis method for by applying the acquisition through the position of the frequency content and sources of traffic lights partial discharge of the acquisition of signal analysis to judge whether a way diagnosis the environment of the scene, and conditions. Partial discharge signal and make the discharge while building blocks were found through the Analysis. Spectrum frequence of Analysis and wide discharge part, to be more precise, in line with the various functions, including the analysis technique band. Diagnosis and comes up with advanced technology that can detect the presence of a position. This method is portable single device developed for maintenance and mobility and ease and convenience of getting caught by discharge of the pattern analysis and position detection method suitable for a new diagnosis will suggest.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.14 no.12
• /
• pp.1032-1040
• /
• 2001

In order to apply the partial discharge measuring technique utilizing electrical pulse to the transformer at sites, this paper describes the measuring technique obtaining only the signals due to internal partial discharge in the transformer, but the noises due to external corona which has been a major problem so far. At first, partial discharge and corona noise were simultaneously generated in the model transformer by using needle-plane electrodes and rod-sphere electrodes out of it in a high voltage laboratory, respectively. It was verified that only the partial discharge signals in the transformer could be measured by removing the noise signals from the superposed signals of partial discharges and noises on the grounding wire of the model transformer. By application to a 345kV transformer in service, it was also confirmed that the partial discharge could be on-line monitored by removing the noise signals measured by the inductance sensor on the grounding wire of a 154kV lightning arrester from the superposed signals of internal partial discharge and external corona noise measured by bushing tap coupler of the transformer.

• Journal of the Institute of Convergence Signal Processing
• /
• v.9 no.3
• /
• pp.173-178
• /
• 2008

In this paper, we present a new impulsive noise detection technique. To remove the impulse noise without detail loss, only corrupted pixels must be filtered. In order to identify the corrupted pixels, a new impulse detector based on rank and value estimations of the current pixel is proposed. Based on the rank and value estimations of the current pixel, the new proposed method provides excellent statistics for detecting an impulse noise while reducing the probability of detecting image details as impulses. The proposed detection is efficient and can be used with any noise removal filter. Simulation results show that the proposed method significantly outperforms many other well-known detection techniques in terms of image restoration and noise detection.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.30 no.5
• /
• pp.389-398
• /
• 2019

In this paper, we propose a method to detect small unmanned aerial vehicles(UAVs) flying in a real-world environment. Small UAV signals are frequently obscured by clutter signals because UAVs usually fly at low altitudes over urban or mountainous terrain. Therefore, to obtain a desirable detection performance, clutter signals must be considered in addition to noise, and thus, a performance analysis of each clutter removal technique is required. The proposed detection process uses clutter removal and pulse integration methods to suppress clutter and noise signals, and then detects small UAVs by utilizing a constant false alarm rate detector. After applying three clutter removal techniques, we analyzed the performance of each technique in detecting small UAVs. Based on experimental data acquired in a real-world outdoor environment, we found it was possible to derive a clutter removal method suitable for the detection of small UAVs.