• Journal of the Korean Society for Nondestructive Testing
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• v.10 no.1
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• pp.47-55
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• 1990

This paper presents experimental results which explore the capability of a CW laser speckle photography for tile measurement of in-plane displacement at high temperature. The serious restrictions on the application of the method seem to be the ambient air turbulence and the change of surface texture caused by the oxidation, as they tend to decorrelate the double exposured speckle patterns. In order to assess only the effect of air turbulence, a ceramics-coated stainless steel plate is heated in air and Ar-laser specklegrams are made with combination of temperature and lateral translation displacement. The slight reduction in visibility of Young's fringes is observed at $1000^{\circ}C$. The analyses of Young's fringes are carried out by a image processing system using a TV-camera and computers, and the result agrees well with the micrometer reading. Futhermore, uncoated stainless steel and Hastelloy X plates are tested and the effect of oxidation is also evaluated. The experimental results demonstrate that a CW laser speckle photography is applicable at temperatures up to $1000^{\circ}C$.

• Current Optics and Photonics
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• v.1 no.1
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• pp.23-28
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• 2017

The laser has been regarded as the potential illumination source for the next generation of projectors. However, currently the major issues in applying the laser as an illumination source for projectors are beam shaping and laser speckle. We present a compact solution for both issues by using a vibrating diffractive optical element (DOE). The DOE is designed and fabricated, and it successfully transforms the circular Gaussian laser beam to a low speckle contrast uniform rectangular pattern. Under a vibration frequency of 150 Hz and amplitude of $200{\mu}m$, the speckle contrast value is reduced from 67.67% to 13.78%, and the ANSI uniformity is improved from 24.36% to 85.54%. The experimental results demonstrate the feasibility and potential of the proposed scheme, and the proposed method is a feasible approach to the miniaturization of laser projection display illumination systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.29-33
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• 2004

This paper presents ESPI system for the measurement of thermal expansion coefficient of STS430 up to 1,000$^{\circ}C$. Existing methods, strain gauge and moire have the limitation of contact to object and do not supply the coefficient up to 800$^{\circ}C$. There needs to measure the data up to 800$^{\circ}C$, because heat resistant materials have high melting temperature up to 1,000$^{\circ}C$. In previous studies related to thermal strain analysis, the quantitative results are not reported by ESPI at high temperature, yet. In-plane ESPI and vacuum chamber for the reduction of air turbulence and oxidation are designed for the measurement of the coefficient up to 1,000$^{\circ}C$and speckle correlation fringe pattern images are processed by commercial image filtering tool-smoothing, thinning and enhancement- to obtain quantitative results, which is compared with references data. The comparison shows two data are agreed within 4.1％ blow 600$^{\circ}C$ however, there is some difference up to 600$^{\circ}C$. Also, the incremental ratio of the coefficient is changed up to 800$^{\circ}C$. The reason is the phase transformation of STS430 probably begins at 800$^{\circ}C$.

• Journal of the Optical Society of Korea
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• v.17 no.1
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• pp.86-90
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• 2013

Various methods have been proposed for enhancing the contrast of laser speckle contrast image (LSCI) in subcutaneous blood flow measurements. However, the LSCI still suffers from low image contrast due to tissue turbidity. Herein, a physicochemical tissue optical clearing (PCTOC) method was employed to enhance the contrast of LSCI. Ex vivo and in vivo experiments were performed with porcine skin samples and male ICR mice, respectively. The ex vivo LSCIs were obtained before and 90 min after the application of the PCTOC and in vivo LSCIs were obtained for 60 min after the application of the PCTOC. In order to obtain the skin recovery images, saline was applied for 30 min after the application of the PCTOC was completed. The visible appearance of the tubing under ex vivo samples and the in vivo vasculature gradually enhanced over time. The LSCI increased as a function of time after the application of the PCTOC in both ex vivo and in vivo experiments, and properly recovered to initial conditions after the application of saline in the in vivo experiment. The LSCI combined with the PCTOC was greatly enhanced even in deep vasculature. It is expected that similar results will be obtained in in vivo human studies.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.595-607
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• 2010

This paper addresses the problem of reducing the speckle noise in SAR images by wavelet transformation, using a non-local means(NLM) filter originated for Gaussian noise removal. Log-transformed SAR image makes multiplicative speckle noise additive. Thus, non-local means filtering and wavelet thresholding are used to reduce the additive noise, followed by an exponential transformation. NLM filter is an image denoising method that replaces each pixel by a weighted average of all the similarly pixels in the image. But the NLM filter takes an acceptable amount of time to perform the process for all possible pairs of pixels. This paper, also proposes an alternative strategy that uses the t-test more efficiently to eliminate pixel pairs that are dissimilar. Extensive simulations showed that the proposed filter outperforms many existing filters terms of quantitative measures such as PSNR and DSSIM as well as qualitative judgments of image quality and the computational time required to restore images.

• Korean Journal of Optics and Photonics
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• v.34 no.5
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• pp.192-201
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• 2023

The band-limited angular spectrum method (BL-ASM) causes aliasing errors due to spatial frequency control problems. In this paper, a sampling interval adjustment technique for phase holograms and a technique for reducing speckle noise and improving image quality using a deep-learningbased U-net model are proposed. With the proposed technique, speckle noise is reduced by first calculating the sampling factor and controlling the spatial frequency by adjusting the sampling interval so that aliasing errors can be removed in a wide range of propagation. The next step is to improve the quality of the reconstructed image by learning the phase hologram to which the deep learning model is applied. In the S/W simulation of various sample images, it was confirmed that the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were improved by 5% and 0.14% on average, compared with the existing BL-ASM.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.93-99
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• 2024

The digital medical imaging, especially, computed tomography (CT), should necessarily be considered in terms of noise distribution caused by converting to X-ray photon to digital imaging signal. Recently, the denoising technique based on deep learning architecture is increasingly used in the medical imaging field. Here, we evaluated noise reduction effect according to various noise types based on the U-net deep learning model in the lung CT images. The input data for deep learning was generated by applying Gaussian noise, Poisson noise, salt and pepper noise and speckle noise from the ground truth (GT) image. In particular, two types of Gaussian noise input data were applied with standard deviation values of 30 and 50. There are applied hyper-parameters, which were Adam as optimizer function, 100 as epochs, and 0.0001 as learning rate, respectively. To analyze the quantitative values, the mean square error (MSE), the peak signal to noise ratio (PSNR) and coefficient of variation (COV) were calculated. According to the results, it was confirmed that the U-net model was effective for noise reduction all of the set conditions in this study. Especially, it showed the best performance in Gaussian noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1098-1110
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• 2003

In this paper, we propose a homomorphic wavelet-based MMSE filter with edge detection to restore images degraded by speckle noise. In the proposed method, a noisy image is first transformed into logarithmic domain. Each pixel in the transformed image is then classified into flat and edge regions by applying DIP operator to the image restored by homomorphic directional MMSE filter. Each pixel in flat region is restored by homomorphic wavelet-based MMSE filter. Each pixel in edge region is restored by the weighted sum of the output of homomorphic wavelet-based MMSE filtering and that of homomorphic directional MMSE filtering. The restored image in spatial domain is finally obtained by applying the exponential function to the restored image in logarithmic domain. Experimental results show that the restored images by the proposed method have ISNR improvement of 3.3-4.0 ㏈ and ${\beta}$, a measurement parameter on edge preservation, improvement of 0.0103-0.0126 and superior subjective image quality over those by conventional methods.

• Journal of the Optical Society of Korea
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• v.12 no.4
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• pp.364-364
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• 2008

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.103-116
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• 2013

Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound(TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Gabor feature extraction and snake-like contour is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing the contour. A Gabor filter bank for extraction of rotation-invariant texture features has been implemented. A support vector machine(SVM) for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted by the snake-like contour algorithm. A number of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with less than 10.2% of the accuracy which is relative to boundary provided manually by experts.