• The Korean Journal of Petroleum Geology
• /
• v.11 no.1 s.12
• /
• pp.9-17
• /
• 2005

In the main target area of the block II, Targe-scale faults occur below the unconformity developed around 1 km in depth. The contrast of seismic velocity around the unconformity is generally so large that the strong multiples and the radical velocity variation would deteriorate the quality of migrated section due to serious distortion. More than 15 kinds of data processing techniques have been applied to improve the image resolution for the structures farmed from this active crustal activity. The bad and noisy traces were edited on the common shot gathers in the first step to get rid of acquisition problems which could take place from unfavorable conditions such as climatic change during data acquisition. Correction of amplitude attenuation caused from spherical divergence and inelastic attenuation has been also applied. Mild F/K filter was used to attenuate coherent noise such as guided waves and side scatters. Predictive deconvolution has been applied before stacking to remove peg-leg multiples and water reverberations. The velocity analysis process was conducted at every 2 km interval to analyze migration velocity, and it was iterated to get the high fidelity image. The strum noise caused from streamer was completely removed by applying predictive deconvolution in time space and ${\tau}-P$ domain. Residual multiples caused from thin layer or water bottom were eliminated through parabolic radon transform demultiple process. The migration using curved ray Kirchhoff-style algorithm has been applied to stack data. The velocity obtained after several iteration approach for MVA (migration velocity analysis) was used instead or DMO for the migration velocity. Using various testing methods, optimum seismic processing parameter can be obtained for structural and stratigraphic interpretation in the Block II, Yellow Sea Basin.

• Journal of Biosystems Engineering
• /
• v.41 no.2
• /
• pp.126-137
• /
• 2016

Purpose: The overall objective of this study was to evaluate the vegetation fraction of soybeans, grown under different cropping conditions using an unmanned aerial vehicle (UAV) equipped with a red, green, and blue (RGB) camera. Methods: Test plots were prepared based on different cropping treatments, i.e., soybean single-cropping, with and without herbicide application and soybean and barley-cover cropping, with and without herbicide application. The UAV flights were manually controlled using a remote flight controller on the ground, with 2.4 GHz radio frequency communication. For image pre-processing, the acquired images were pre-treated and georeferenced using a fisheye distortion removal function, and ground control points were collected using Google Maps. Tarpaulin panels of different colors were used to calibrate the multi-temporal images by converting the RGB digital number values into the RGB reflectance spectrum, utilizing a linear regression method. Excess Green (ExG) vegetation indices for each of the test plots were compared with the M-statistic method in order to quantitatively evaluate the greenness of soybean fields under different cropping systems. Results: The reflectance calibration methods used in the study showed high coefficients of determination, ranging from 0.8 to 0.9, indicating the feasibility of a linear regression fitting method for monitoring multi-temporal RGB images of soybean fields. As expected, the ExG vegetation indices changed according to different soybean growth stages, showing clear differences among the test plots with different cropping treatments in the early season of < 60 days after sowing (DAS). With the M-statistic method, the test plots under different treatments could be discriminated in the early seasons of <41 DAS, showing a value of M > 1. Conclusion: Therefore, multi-temporal images obtained with an UAV and a RGB camera could be applied for quantifying overall vegetation fractions and crop growth status, and this information could contribute to determine proper treatments for the vegetation fraction.

• Journal of Broadcast Engineering
• /
• v.14 no.2
• /
• pp.144-153
• /
• 2009

Recently, as the necessity of a light-weighted video encoding technique has been rising for applications such as UCC(User Created Contents) or Multiview Video, Distributed Video Coding(DVC) where a decoder, not an encoder, performs the motion estimation/compensation taking most of computational complexity has been vigorously investigated. Wyner-Ziv coding reconstructs an image by eliminating the noise on side information which is decoder-side prediction of original image using channel code. Generally the side information of Wyner-Ziv coding is generated by using frame interpolation between key frames. The channel code such as Turbo code or LDPC code which shows a performance close to the Shannon's limit is employed. The noise model of Wyner-Ziv coding for channel decoding is called Virtual Channel Noise and is generally modeled by Laplacian or Gaussian distribution. In this paper, we propose a Wyner-Ziv coding method based on the frequency-adaptive channel noise modeling in transform domain. The experimental results with various sequences prove that the proposed method makes the channel noise model more accurate compared to the conventional scheme, resulting in improvement of the rate-distortion performance by up to 0.52dB.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.12
• /
• pp.7324-7330
• /
• 2014

Color distortion of the dark images acquired under a low-light-level environment with a weak light source can be cause of the performance decreation of various vision systems. Therefore, recovering the original color of the images is an important process for enhancing the performance of the system. For this, this study proposes a color restoration method using a dichromatic reflection model. This paper assumes that the dark images can be classified into two parts affected by specular or diffuse reflection. Two different color constancy methods were then applied to the images to remove the effects of each reflection and two images were created as a result. The resulting images produced a one color-corrected image by combining with different weights according to the position in the images. For the performance evaluation, this paper used a synthesized image, and considered the Euclidean distance and angular error as an evaluation factor. In addition, a performance comparison was performed with the existing various color constancy method to achieve the objectivity of evaluation. The experimental results showed that the proposed method can be a more suitable solution for color restoration than the existing method.

• Journal of the Korea Computer Graphics Society
• /
• v.25 no.5
• /
• pp.1-9
• /
• 2019

In this paper, we propose a video enhancement method using generative adversarial networks to remove raindrops and restore the background information on the removed region in the coastal wave video imagery distorted by raindrops during rainfall. Two experimental models are implemented: Pix2Pix network widely used for image-to-image translation and Attentive GAN, which is currently performing well for raindrop removal on a single images. The models are trained with a public dataset of paired natural images with and without raindrops and the trained models are evaluated their performance of raindrop removal and background information recovery of rainwater distortion of coastal wave video imagery. In order to improve the performance, we have acquired paired video dataset with and without raindrops at the real coast and conducted transfer learning to the pre-trained models with those new dataset. The performance of fine-tuned models is improved by comparing the results from pre-trained models. The performance is evaluated using the peak signal-to-noise ratio and structural similarity index and the fine-tuned Pix2Pix network by transfer learning shows the best performance to reconstruct distorted coastal wave video imagery by raindrops.

• Journal of the Korea Convergence Society
• /
• v.11 no.2
• /
• pp.53-60
• /
• 2020

The purpose of this paper is to evaluate the image of the Styrofoam Wedge that can minimize the position change by supporting the wrist during the True PA and lateral examination of the wrist. In 50 people, the gap between the distal radius joint facet and the wrist bone was measured after the wrist True PA and lateral images were obtained using a general examination(vertical), tube angle(vertical:10°, lateral:20°) and Styrofoam Wedge(vertical). When joint spacing was measured in the True PA and lateral images of the wrist, general examination(5.54mm, 9.42mm), tube angle(2.05mm, 5.07mm) and Styrofoam Wedge(1.79mm, 5.46mm) were shown to be small. The smaller the joint spacing, the easier it is to observe that is open. Therefore, True PA and lateral imaging of the wrist Styrofoam Wedge can reduce the distortion of the image and thus acquire images of high diagnostic value. In addition, it may be possible to reduce the deviation caused by the change of patient's position during re-projection.

• The KIPS Transactions:PartB
• /
• v.11B no.3
• /
• pp.309-316
• /
• 2004

In this paper, we proposed the TDS(T-shape Diamond Search) based on the directions of above, below, left and right points to estimate the motion vector fast and more correctly in this method, we exploit the facts that most motion vectors are enclosed in a circular region with a radius of 2 fixels around search center(0,0). At first, the 4 points in the above, below, left and right around the search center is calculated to decide the point of the MBD(Minimum Block Distortion). And then w. above point of the MBD is checked to calculate the SAD. If the SAD of the above point is less than the previous MBD, this process is repeated. Otherwise, the right and left points of MBD are calculated to decide The points that have the MBD between right point and left point. Above processes are repeated to the predicted direction for motion estimation. Especially, if the motions of image are concentrated in the crossing directions, the points of other directions are omitted. As a result, we can estimate motion vectors fast. Experiments show that the speedup improvement of the proposed algorithm over Diamond Search algorithm(DS) and HEXgon Based Search(HEXBS) can be up to 38∼50％ while maintaining similar image Quality.

• Culinary science and hospitality research
• /
• v.22 no.2
• /
• pp.78-92
• /
• 2016

This study investigated the quality characteristics of white pan bread with banana addition. This analysis was through mixograph and stickiness of dough, fermentation rate, TPA, crumbScan image analysis, color, moisture contents and acceptance test. Mixograph peak time presented 4~5 minutes on every sample. However, CON, B10 and B20 sample presented more than 60%, and B30, B40 presented less than 60% at peak value (%). The result indicated that banana addition increased as the stickiness decreased. The fermentation rate generally increased, but the sample B40 decreased after 75 minutes. The result of crust and inside color, CON was the highest on lightness L value, B40 was the highest on both red a value and yellow b value. The result of pH showed that B40 was the lowest, and more banana addition made pH decreased. Thus, adding banana influences negatively on volume and cost of the product. The image analysis through crumbScan did not show any significant difference on crust thickness and distortion of crumb fineness. On the other hand, CON value was 774.33 that was the lowest, and B40 value was 927.66 which is the highest on the density of crumb fineness. Hardness showed a significant difference; B40 was the lowest, and Control was the highest. Moisture contents generally had a noticeable difference; CON value was the highest, and banana addition increased as the value decreased. At the result of acceptance test, one of the sensory tests, B20 showed the highest grade, and B40 showed the worst. Based on the above results of characteristic difference, banana addition could influence volume of the bread negatively.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.1
• /
• pp.128-138
• /
• 2010

In this paper, we propose a new bit assignment scheme for Wyner-Ziv video coding. Distributed video coding (DVC) is a new video coding paradigm which enables greatly low complexity encoding because it does not have any motion prediction module at encoder. Therefore, it is very well suited for many applications such as video communication, video surveillance, extremely low power consumption video coding, and other portable applications. Theoretically, the Wyner-Ziv video coding is proved to achieve the same rate-distortion (RD) performance comparable to that of the joint video coding. However, its RD performance has much gap compared to MC-DCT-based video coding such as H.264/AVC. Moreover, Transform Domain Wyner-Ziv (TDWZ) video coding which is a kind of DVC with transform module has difficulty of exact bit assignment because the entire image is treated as a same message. In this paper, we propose a feasible bit assignment algorithm using adaptive quantization matrix selection for the TDWZ video coding. The proposed method can calculate suitable bit amount for each region using the local characteristics of image. Simulation results show that the proposed method can enhance coding performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.27 no.6
• /
• pp.566-576
• /
• 2016

Inverse synthetic aperture radar(ISAR) image generated from bistatic radar(Bi-ISAR) represents two-dimensional scattering distribution of a target, and the Bi-ISAR can be used for bistatic target identification. However, Bi-ISAR has large variability in scattering mechanisms depending on bistatic configurations and do not represent exact range-Doppler information of a target due to inherent distortion. Thus, an efficient training DB construction is the most important factor in target identification using Bi-ISARs. Recently, a database construction method based on realistic flight scenarios of a target, which provides a reliable identification performance for the monostatic target identification, was applied to target identification using high resolution range profiles(HRRPs) generated from bistatic radar(Bi-HRRPs), to construct efficient training DB under bistatic configurations. Consequently, high identification performance was achieved using only small amount of training Bi-HRRPs, when the target is a considerable distance away from the bistatic radar. Thus, flight scenarios based training DB construction is applied to target identification using Bi-ISARs. Then, the capability and efficiency of the method is analyzed.