• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.1
• /
• pp.43-48
• /
• 2014

Usually, image deconvolution is applied as a preprocessing step in surveillance systems to reduce the effect of motion or out-of-focus blur problem. In this paper, we propose a blind-image deconvolution filtering approach based on genetic programming (GP). A numerical expression is developed using GP process for image restoration which optimally combines and exploits dependencies among features of the blurred image. In order to develop such function, first, a set of feature vectors is formed by considering a small neighborhood around each pixel. At second stage, the estimator is trained and developed through GP process that automatically selects and combines the useful feature information under a fitness criterion. The developed function is then applied to estimate the image pixel intensity of the degraded image. The performance of developed function is estimated using various degraded image sequences. Our comparative analysis highlights the effectiveness of the proposed filter.

• Korean Journal of Remote Sensing
• /
• v.25 no.5
• /
• pp.455-464
• /
• 2009

Lee(2009) proposed the boundary-adaptive despeckling method using a Bayesian model which is based on the lognormal distribution for image intensity and a Markov random field(MRF) for image texture. This method employs the Point-Jacobian iteration to obtain a maximum a posteriori(MAP) estimate of despeckled imagery. The boundary-adaptive algorithm is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The boundary-adaptive scheme was comprehensively evaluated using simulation data and the effectiveness of boundary adaption was proved in Lee(2009). This study, as an extension of Lee(2009), has suggested a modified iteration algorithm of MAP estimation to enhance computational efficiency and to combine classification. The experiment of simulation data shows that the boundary-adaption results in yielding clear boundary as well as reducing error in classification. The boundary-adaptive scheme has also been applied to high resolution Terra-SAR data acquired from the west coast of Youngjong-do, and the results imply that it can improve analytical accuracy in SAR application.

• Journal of Korea Water Resources Association
• /
• v.56 no.6
• /
• pp.403-417
• /
• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Spatial Information Research
• /
• v.19 no.5
• /
• pp.1-11
• /
• 2011

This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.43 no.5 s.311
• /
• pp.29-37
• /
• 2006

Thresholding is a fundamental approach to segmentation that utilizes a significant degree of pixel popularity or intensity. Otsu's thresholding employed the normalized histogram as a discrete probability density function. Also it utilized a criterion that minimizes the between-class variance of pixel intensity to choose a threshold value for segmentation. However, the Otsu's method has a disadvantage of repeatedly searching optimal thresholds for the entire range. In this paper, a simple but fast multi-level thresholding approach is proposed by means of extending the Otsu's method. Rather than invoke the Otsu's method for the entire gray range, we advocate that the gray-level range of an image be first divided into smaller sub-ranges, and that the multi-level thresholds be achieved by iteratively invoking this dividing process. Initially, in the proposed method, the gray range of the object image is divided into 2 classes with a threshold value. Here, the threshold value for segmentation is selected by invoking the Otsu's method for the entire range. Following this, the two classes are divided into 4 classes again by applying the Otsu's method to each of the divided sub-ranges. This process is repeatedly performed until the required number of thresholds is obtained. Our experimental results for three benchmark images and fifty faces show a possibility that the proposed method could be used efficiently for pattern matching and face recognition.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.2
• /
• pp.52-63
• /
• 2021

In previous research, the coastal wetlands were detected by using the vegetation indices or land cover classification maps derived from the multispectral bands of the satellite or aerial imagery, and this approach caused the various limitations for detecting the coastal wetlands with high accuracy due to the difficulty of acquiring both land cover and topographic information by using the single remote sensing data. This research suggested the efficient methodology for detecting the coastal wetlands using the sentinel-2 satellite image and SRTM(Shuttle Radar Topography Mission) DEM (Digital Elevation Model) acquired in Gomsoman Bay, west coasts of South Korea through the following steps. First, the NDWI(Normalized Difference Water Index) image was generated using the green and near-infrared bands of the given Sentinel-2 satellite image. Then, the binary image that separating lands and waters was generated from the NDWI image based on the pixel intensity value 0.2 as the threshold and the other binary image that separating the upper sea level areas and the under sea level areas was generated from the SRTM DEM based on the pixel intensity value 0 as the threshold. Finally, the coastal wetland map was generated by overlaying analysis of these binary images. The generated coastal wetland map had the 94% overall accuracy. In addition, the other types of wetlands such as inland wetlands or mountain wetlands were not detected in the generated coastal wetland map, which means that the generated coastal wetland map can be used for the coastal wetland management tasks.

• Convergence Security Journal
• /
• v.13 no.3
• /
• pp.9-15
• /
• 2013

Calculating of matching cost is an important for efficient stereo matching. To investigate the performance of matching process, the concepts of the existing methods are introduced. Also we analyze the performance and merits of them. The simplest matching costs assume constant intensities at matching image locations. We consider matching cost functions which can be distinguished between pixel-based and window-based approaches. The Pixel-based approach includes absolute differences (AD) and sampling-intensitive absolute differences (BT). The window-based approach includes the sum of the absolute differences, the sum of squared differences, the normalized cross-correlation, zero-mean normalized cross-correlation, census transform, and the absolute differences census transform (AD-Census). We evaluate matching cost functions in terms of accuracy and time complexity. In terms of the accuracy, AD-Census method shows the lowest matching error ratio (the best solution). The ZNCC method shows the lowest matching error ratio in non-occlusion and all evaluation part. But it performs high matching error ratio at the discontinuities evaluation part due to blurring effect in the boundary. The pixel-based AD method shows a low complexity in terms of time complexity.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.14 no.4
• /
• pp.269-274
• /
• 2021

In secret communication, steganography is the sending and receiving of secret messages without being recognized by a third party. In the spatial domain method bitwise information is inserted into the virtual bit plane of the decomposed pixel values of the image. That is, the bitwise secret message is sequentially inserted into the least significant bit(LSB) of the image, which is a cover medium. In terms of application, the LSB is simple, but has a drawback that can be easily detected by a third party. If the upper bit plane is used to increase security, the image quality may deteriorate. In this paper, I present a method for concealing Hangul secret messages in image steganography based on the lo-th bit plane and the decomposition of modified pixel intensity values. After decomposing the Hangeul message to be hidden into choseong, jungseong and jongseong, then a shuffling process is applied to increase confidentiality and robustness. PSNR was used to confirm the efficiency of the proposed method. It was confirmed that the proposed technique has a smaller effect in terms of image quality than the method applying BCD and Fibonacci when inserting a secret message in the upper bit plane. When compared with the reference value, it was confirmed that the PSNR value of the proposed method was appropriate.

• Journal of The Korean Astronomical Society
• /
• v.54 no.2
• /
• pp.49-60
• /
• 2021

Observations of line of sight (LOS) Doppler velocity and non-thermal line width in the off-limb solar corona are often used for investigating the Alfvén wave signatures in the corona. In this study, we compare LOS Doppler velocities and non-thermal line widths obtained simultaneously from two different instruments, Coronal Multichannel Polarimeter (CoMP) and Hinode/EUV Imaging Spectrometer (EIS), on various off-limb coronal regions: flaring and quiescent active regions, equatorial quiet region, and polar prominence and plume regions observed in 2012-2014. CoMP provides the polarization at the Fe xiii 10747 Å coronal forbidden lines which allows their spectral line intensity, LOS Doppler velocity, and line width to be measured with a low spectral resolution of 1.2 Å in 2-D off limb corona between 1.05 and 1.40 RSun, while Hinode/EIS gives us the EUV spectral information with a high spectral resolution (0.025 Å) in a limited field of view raster scan. In order to compare them, we make pseudo raster scan CoMP maps using information of each EIS scan slit time and position. We compare the CoMP and EIS spectroscopic maps by visual inspection, and examine their pixel to pixel correlations and percentages of pixel numbers satisfying the condition that the differences between CoMP and EIS spectroscopic quantities are within the EIS measurement accuracy: ±3 km s-1 for LOS Doppler velocity and ±9 km s-1 for non-thermal width. The main results are summarized as follows. By comparing CoMP and EIS Doppler velocity distributions, we find that they are consistent with each other overall in the active regions and equatorial quiet region (0.25 ≤ CC ≤ 0.7), while they are partially similar to each other in the overlying loops of prominences and near the bottom of the polar plume (0.02 ≤ CC ≤ 0.18). CoMP Doppler velocities are consistent with the EIS ones within the EIS measurement accuracy in most regions (≥ 87% of pixels) except for the polar region (45% of pixels). We find that CoMP and EIS non-thermal width distributions are similar overall in the active regions (0.06 ≤ CC ≤ 0.61), while they seem to be different in the others (-0.1 ≤ CC ≤ 0.00). CoMP non-thermal widths are similar to EIS ones within the EIS measurement accuracy in a quiescent active region (79% of pixels), while they do not match in the other regions (≤ 61% of pixels); the CoMP observations tend to underestimate the widths by about 20% to 40% compared to the EIS ones. Our results demonstrate that CoMP observations can provide reliable 2-D LOS Doppler velocity distributions on active regions and might provide their non-thermal width distributions.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.9
• /
• pp.4068-4074
• /
• 2011

The purpose of this study was to examine the usefulness of MR Breast perfusion image and time-signal intensity curve in patients diagnosed with breast cancer. We selected on 20 patients who were histologically diagnosed to have invasive ductal carcinoma (IDC) from March 2009 to December 2010. First, the Breast perfusion mapping image was reconstructed after obtaining the dynamic contrast enhancement image. The reconstructed image measured the slope, maximal relative enhancement, and time to peak on the detail including the lesion region, normal region, back ground region after obtaining the time-signal intensity curve. The lesion region and normal and slope of the back ground part were measured with the quantitive analytical method about the research and the average was compared and was analyze. In the qualitative analysis, the signal strength of each pixel was analyze with the macroscopic and being high it was low, the medium (2) performed the division of (a) by the three-point standard and the average was measured. The findings from the quantitative image analysis are the following: In the lesion region, the slope and maximal relative enhancement were the highestest among and the time to peak was the highestest in the back ground region. In the qualitative analysis, the breast perfusion image showed a diagnostic efficiency.