• Journal of Biomedical Engineering Research
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• v.37 no.4
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• pp.140-146
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• 2016

The ultrasound imaging in medical diagnosis has become a popular modality because of its safe, noninvasive, portable, relatively inexpensive, and provides a real-time image formation. However, usefulness of ultrasound imaging is at times limited due to the presence of signal-dependent noise like as speckle. Therefore, noise reduction is very important, as various types of noise generated limits the effectiveness of medical image diagnosis. This paper introduces a speckle noise reduce algorithm using total variation denoising (TVD) in Laplacian pyramid. With this method, speckle is removed by TVD of bandpass ultrasound images in Laplacian pyramid domain. For TVD in each pyramid layer, a ${\lambda}$ is selected by trial-and-error method. The visual comparison of despeckled 'in vivo' ultrasound images from pancreas shows that the proposed method could effectively preserve edges and detailed structures while thoroughly suppressing speckle. For a Simulated B-mode image, contrast-to-noise-ratio (CNR) and signal-to-noise-ratio (SNR) were obtained like 4.65 dB and 14.11 dB, respectively. The results show that the proposed method can conduct better than some of the existing methods in terms of the CNR and the SNR.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.33-42
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. MRFs have been used to model spatially correlated and signal-dependent phenomena for SAR speckled images. The MRF is incorporated into digital image analysis by viewing pixel types as slates of molecules in a lattice-like physical system defined on a GRF Because of the MRF-SRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular interactions. The proposed Point-Jacobian Iterative MAP estimation method was first evaluated using simulation data generated by the Monte Carlo method. The methodology was then applied to data acquired by the ESA's ERS satellite on Nonsan area of Korean Peninsula. In the extensive experiments of this study, The proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.126-129
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel type s as states of molecules in a lattice-like physical system defined on a GRF. Because of the MRFGRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular mteractions. The proposed adaptive iterative method was evaluated using simulation data generated by the Monte Carlo method. In the extensive experiments of this study, the proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.455-464
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• 2007

Lee(2007) suggested the Point-Jacobian iteration MAP estimation(PJIMAP) for noise removal of the images that are corrupted by multiplicative speckle noise. It is to find a MAP estimation of noisy-free imagery based on a Bayesian model using the lognormal distribution for image intensity and an MRF for image texture. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. In this study, the MAP estimation is computed by the Point-Jacobian iteration using adaptive parameters. At each iteration, the parameters related to the Bayesian model are adaptively estimated using the updated information. The results of the proposed scheme were compared to them of PJIMAP with SAR simulation data generated by the Monte Carlo method. The experiments demonstrated an improvement in relaxing speckle noise and estimating noise-free intensity by using the adaptive parameters for the Ponit-Jacobian iteration.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.705-719
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• 2010

We investigated the speckle filtering effect in supervised classification of the C-band polarimetric Ground Based SAR image data. Wishart classification method was used for the supervised classification of the polarimetric GB-SAR image data and total of 6 kinds of speckle filters were applied before supervised classification, which are boxcar, Gaussian, Lopez, IDAN, the refined Lee, and the refined Lee sigma filters. For each filters, we changed the filtering kernel size from $3{\times}3$ to $9{\times}9$ to investigate the filtering size effect also. The refined Lee filter with the kernel size of bigger than $5{\times}5$ showed the best result for the Wishart supervised classification of polarimetric GB-SAR image data. The result also showed that the type of trees could be discriminated by Wishart supervised classification of polarimetric GB-SAR image data.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1382-1390
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• 1995

Electronic Speckle Pattern Interferometry (ESPI) with a CW laser, a video system and an image processor was utilized to measure the in-plane displacement. Unlike traditional strain gauges or Moire method. ESPI method measure the in-plane displacement on real time with out any surface preparation on surface attachment. The specimen has a crack of 10*0.1 mm in the middle of plate and strain gauge was also attached on that surface to compare with ESPI method. This study reveled the ESPI method to measure the displacement and distribution of strain in the specimen. It was shown in tensile tests that the measurement by ESPI method was comparable with strain gauge.

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.8-12
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• 2016

In this paper, we theoretically and experimentally analyze the impact of speckle size of pseudo-thermal light source on ghost imaging. A larger size of speckle can bring improvements in SNR and visibility. At the same time, the edge blur of the retrieved image will become more serious. We also present a setup which can mitigate the edge blur of larger speckle while maintaining the advantages of higher SNR and visibility by changing the speckle size of the object beam with a concave lens.

• Transactions of the Society of Information Storage Systems
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• v.10 no.2
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• pp.55-60
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• 2014

Laser projector has many advantages of high brightness, high resolution and small size, but the huge drawback of image degradation called speckle which generated by coherence of laser and roughness of surface interrupts their general use. There are many methods to reduce speckle pattern, but they need effective optical systems to realize display to the far field with huge volume. We designed speckle reduction element by using microlens with controlled curvature to reduce spatial coherence. Vibration element was also applied to reduce temporal coherence which considered response time of eye. Designed element was fabricated by simple reflow method and imprinting method. From the results, the fabricated element performed 48.33% of speckle reduction efficiency and 41.29% of optical efficiency with a single doublet lens.

• Current Optics and Photonics
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• v.3 no.3
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• pp.220-226
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• 2019

A novel speckle-shifting ghost imaging (SSGI) technique is proposed in this paper. This method can effectively extract the edge of an unknown object without achieving its clear ghost image beforehand. However, owing to the imaging mechanism of SSGI, the imaging result generally contains serious noise. To solve the problem, we further propose a simple and effective method to remove noise from the speckle-shifting ghost image with a connected-region labeling (CRL) algorithm. In this method, two ghost images of an object are first generated according to SSGI. A threshold and the CRL are then used to remove noise from the imaging results in turn. This method can retrieve a high-quality image of an object with fewer measurements. Numerical simulations are carried out to verify the feasibility and effectiveness.

• Current Optics and Photonics
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• v.5 no.4
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• pp.362-369
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• 2021

Absolute position sensors are widely used in machine tools and precision measuring instruments because measurement errors are not accumulated, and position measurements can be performed without initialization. The laser speckle-based absolute position sensor, in particular, has advantages in terms of simple system configuration and high measurement accuracy. Unlike traditional absolute position sensors, it does not require an expensive physical length scale; instead, it uses a laser speckle image database to measure a moving surface position. However, there is a problem that a huge database is required to store information in all positions on the surface. Conversely, reducing the size of the database also decreases the accuracy of position measurements. Therefore, in this paper, we propose a new method to measure the surface position with high precision while reducing the size of the database. We use image stitching and approximation methods to reduce database size and speed up measurements. The absolute position error of the proposed method was about 0.27 ± 0.18 ㎛, and the average measurement time was 25 ms.