• 한국가시화정보학회:학술대회논문집
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• 2001.12a
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• pp.123-137
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• 2001

PIV (particle image velocimetry) systems use a camera to take snapshots of particles carried by a fluid at some precise instants. Signal processing methods are then used to compute the flow velocity field. In this paper, the design of the camera objective (optics) is addressed. The optimization is done in order to maximize the signal-to-noise ratio of in-focus particles. Four different kinds of noise are considered: photon shot noise, thermal and read noise, background glow shot noise, and noise made by the other particles. A semi-empirical model for the lens aberrations of a two-doublet objective is first addressed, since further, it is shown that lens aberrations (low f-value $f_{\#}$) should be used instead of the Fraunhofer diffraction (high f-value) for the fitting of the particle image size with the pixel size. Other important conclusions of the paper include the expression of optimum values for the magnification M, for the exposure period $\tau$ and for the pixel size $\xi$.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.2 s.119
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• pp.160-167
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• 2007

In this study, the influences of environmentally friendly visual and auditory information on traffic noise perception were surveyed by the using electroencephalogram. Green rural region image and CBD (central business district) image in urban city were used as visual informations. And traffic noise, signal and environmental music were used to detect the impact on electroencephalogram variance. It was revealed that green rural region image caused ${\alpha}-wave$ ratio increase about 10% and environmental music increased ${\alpha}-wave$ ratio approximately $40{\sim}50%$. The results of this study improved that environmentally friendly visual and auditory information had an effect on decreasing traffic noise loudness to some extents.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.75-80
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• 2008

The impulse noise is very common and typical noise in the digital image. Many methods are invented in order to remove the impulse noise since the development of Digital Image Processing. For example, the median filter has been used for removing the impulse noise. In this paper, we try to remove the impulse noise using wavelet transformation in the wavelet-transformed detail areas. We also compare the algorithm with median filter with the visual and numerical methods. The result using the algorithm in this paper was much better than the median filter in both removing the noise and keeping the edges. The proposed algorithm needs more calculating time but has more advantages than the median filter has.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.581-584
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• 2005

The performance of printer can be determined lots of factors such as the printing speed, resolution, image quality, first page out time, paper handling performance and acoustic noise. Among them, acoustic noise and image quality are closely related to the mechanism vibration in the printing operation. To improve these quality, it is important to understand the functions of all individual parts and their relations to entire system. In this paper, the principle of LBP is briefly explained and then the characteristics of printing noise and image banding are explained.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1540-1546
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• 2017

Digital image processing is widely used in various fields including the military, medical, image recognition system, robot and commercial sectors. But in the process of acquiring and transmitting digital images, noise is generated by various external causes. There are various types of general noise depending on the cause and form, but AWGN and impulse noise is one of the leading methods. Removing noise during image processing is essential to the pre-treatment process such as segmentation, image recognition and characteristic extraction. As such, this paper suggests an algorithm that distinguishes the non-edge area and edge area using the Canny edge to apply different filters to different areas in order to effectively remove noise from the image. To verify the effectiveness of the suggested algorithm, it was compared against existing methods using zoom images, edge images and PSNR(peak signal to noise ratio).

• Journal of radiological science and technology
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• v.44 no.4
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• pp.327-333
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• 2021

Magnetic resonance imaging(MRI) uses strong magnetic field to image the cross-section of human body and has excellent image quality with no risk of radiation exposure. Because of above-mentioned advantages, MRI has been widely used in clinical fields. However, the noise generated in MRI degrades the quality of medical images and has a negative effect on quick and accurate diagnosis. In particular, examining a object with a detailed structure such as brain, image quality degradation becomes a problem for diagnosis. Therefore, in this study, we acquired T2 weighted 3D data of multiple sclerosis disease using BrainWeb simulation program, and used quantitative evaluation factors to find appropriate slice thickness among 1, 3, 5, and 7 mm. Coefficient of variation and contrast to noise ratio were calculated to evaluate the noise level, and root mean square error and peak signal to noise ratio were used to evaluate the similarity with the reference image. As a result, the noise level decreased as the slice thickness increased, while the similarity decreased after 5 mm. In conclusion, as the slice thickness increases, the noise is reduced and the image quality is improved. However, since the edge signal is lost due to overlapped signal, it is considered that selecting appropriate slice thickness is necessary.

• Journal of radiological science and technology
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• v.46 no.6
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• pp.475-484
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• 2023

This study aimed to compare filters for reducing speckle noise in ultrasound images using clinical liver images. We acquired the clinical liver ultrasound images, and noisy images were obtained by adding 0.01, 0.05, 0.10, and 0.50 intensity levels of speckle noise to the liver images. The Wiener filter, median modified Wiener filter, gamma filter, and Lee filter were designed for the noisy images by setting window sizes at 3×3, 5×5, and 7×7. The coefficient of variation (COV) and contrast to noise ratio (CNR) were calculated to evaluate noise reduction and various filters. Moreover, the filter with the highest image quality was selected and quantitatively compared to a noisy image. As a result, COV and CNR showed the noise improved result when the Lee filter was applied. Furthermore, the Lee filter image with a window size of 7×7 was noted to possess approximately a minimum of 1.28 to a maximum of 3.38 times better COV and a minimum of 2.18 to a maximum of 5.50 times better CNR than the noisy image. In conclusion, we confirmed that the Lee filter was effective in reducing speckle noise and proved that an appropriate window size needs to be set considering blurring.

• Journal of radiological science and technology
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• v.47 no.2
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• pp.117-123
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• 2024

This study was to assessment of quality assurance (QA) and noise characteristics of Noise Power Spectrum (NPS) according to the time of by using electronic portal imaging device (EPID) for LINAC (Linear Accelerator). LINAC device was (Varian Clinac^R iX LINAC, USA) used and the were 40 × 30 cm² of detector size were 1024 × 768 photo-electric diode array size. Signal could be obtained the K-space image of white noise images for NPS and we used to Overlap, Non-Overlap, Out of Penumbra, Flatness, Symmetry, Symmetry Rt, Lt methods. The 2013s NPS image Out of Penumbra quantitatively value more than 2013s NPS image Symmetry Rt, Lt methods quantitatively NPS based on the frequency of 1.0 mm^-1. Thus, the 2022s NPS image Out of Penumbra quantitatively value more than 2022s NPS image Symmetry Rt, Lt methods quantitatively NPS based on the frequency of 1.0 mm^-1. The assessment of comparison of white noise for NPS image noise and intensity of this study were to that should be used efficiently of the LINAC EPID detector system for Overlap method for International Electro-technical Commission (IEC).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.1
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• pp.74-82
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• 2008

The objective of this paper is to remove noises of image based on the heuristic noises filter and to extract a tumor region by using morphology techniques in breast ultrasound image. Similar objective studies have been conducted based on ultrasound image of high resolution. As a result, efficiency of noise removal is not fine enough for low resolution image. Moreover, when ultrasound image has multiple tumors, the extraction of ROI (Region Of Interest) is not accomplished or processed by a manual selection. In this paper, our method is done 4 kinds of process for noises removal and the extraction of ROI for solving problems of restrictive automated segmentation. First process is that pixel value is acquired as matrix type. Second process is a image preprocessing phase that is aimed to maximize a contrast of image and prevent a leak of personal information. In next process, the heuristic noise filter that is based on opinion of medical specialist is applied to remove noises. The last process is to extract a tumor region by using morphology techniques. As a result, the noise is effectively eliminated in all images and a extraction of tumor regions is possible though one ultrasound image has several tumors.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.535-538
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.