• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.303-319
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• 2015

The objectives of this paper are to measure surface imperviousness using three different classification methods: per-pixel, sub-pixel, and object-oriented classification. They are tested on high-spatial resolution QuickBird data at 2.4 meters (four spectral bands and three principal component bands) as well as a medium-spatial resolution Landsat TM image at 30 meters. To measure impervious surfaces, we selected 30 sample sites with different land uses and residential densities across image representing the city of Phoenix, Arizona, USA. For per-pixel an unsupervised classification is first conducted to provide prior knowledge on the possible candidate spectral classes, and then a supervised classification is performed using the maximum-likelihood rule. For sub-pixel classification, a Linear Spectral Mixture Analysis (LSMA) is used to disentangle land cover information from mixed pixels. For object-oriented classification several different sets of scale parameters and expert decision rules are implemented, including a nearest neighbor classifier. The results from these three methods show that the object-oriented approach (accuracy of 91%) provides more accurate results than those achieved by per-pixel algorithm (accuracy of 67% and 83% using Landsat TM and QuickBird, respectively). It is also clear that sub-pixel algorithm gives more accurate results (accuracy of 87%) in case of intensive and dense urban areas using medium-resolution imagery.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.1-6
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• 2019

Foreground/background segmentation in video sequences is often one of the first tasks in machine vision applications, making it a critical part of the system. In this paper, we present an improved sample-based technique that provides robust background image as well as segmentation mask. The conventional multiple interval sampling (MIS) algorithm have suffer from the unbalance of computation time per frame and the rapid change of confidence factor of background pixel. To balance the computation amount, a random-based pixel update scheme is proposed and a spatial and temporal smoothing technique is adopted to increase reliability of the confidence factor. The proposed method allows the sampling queue to have more dispersed data in time and space, and provides more continuous and reliable confidence factor. Experimental results revealed that our method works well to estimate stable background image and the foreground mask.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1507-1510
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• 2003

We propose UPGMA(Unweighted Pair Group Method using Average distance) as hierarchical clustering to detect abrupt shot changes using multiple features such as pixel-by-pixel difference, global and local histogram difference. Conventional $\kappa$-means algorithm which is a method of the partitional clustering, has to select an efficient initial cluster center adaptively UPGMA that we propose, does not need initial cluster center because of agglomerative algorithm that it starts from each sample for clusters. And UPGMA results in stable performance. Experiment results show that the proposed algorithm works not only well but also stably.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1533-1536
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• 2003

In this paper, instead of conventional color management method that using spectrum analysis, a simplified color management scheme is proposed that is low-cost required method to reproduce the visual color perception of human. Proposed scheme uses computer color scanner to obtain a bit map image from dyed original color sample, and conducts pixel analysis by image histogram. From obtained image histogram, extract the color and RGB value from histogram that shows dominant pixel distribution of the sample image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.456-477
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• 2024

With information technology's rapid development, the Internet faces serious security problems. Studies have shown that malware has become a primary means of attacking the Internet. Therefore, adversarial samples have become a vital breakthrough point for studying malware. By studying adversarial samples, we can gain insights into the behavior and characteristics of malware, evaluate the performance of existing detectors in the face of deceptive samples, and help to discover vulnerabilities and improve detection methods for better performance. However, existing adversarial sample generation methods still need help regarding escape effectiveness and mobility. For instance, researchers have attempted to incorporate perturbation methods like Fast Gradient Sign Method (FGSM), Projected Gradient Descent (PGD), and others into adversarial samples to obfuscate detectors. However, these methods are only effective in specific environments and yield limited evasion effectiveness. To solve the above problems, this paper proposes a malware adversarial sample generation method (PixGAN) based on the pixel attention mechanism, which aims to improve adversarial samples' escape effect and mobility. The method transforms malware into grey-scale images and introduces the pixel attention mechanism in the Deep Convolution Generative Adversarial Networks (DCGAN) model to weigh the critical pixels in the grey-scale map, which improves the modeling ability of the generator and discriminator, thus enhancing the escape effect and mobility of the adversarial samples. The escape rate (ASR) is used as an evaluation index of the quality of the adversarial samples. The experimental results show that the adversarial samples generated by PixGAN achieve escape rates of 97%, 94%, 35%, 39%, and 43% on the Random Forest (RF), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Convolutional Neural Network and Recurrent Neural Network (CNN_RNN), and Convolutional Neural Network and Long Short Term Memory (CNN_LSTM) algorithmic detectors, respectively.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.363-370
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• 2003

This paper describes a rectification procedure that relies on a polynomial model derived from the imaging geometry without loss of accuracy. By using polynomial model, one can effectively eliminate the iterative process to find an image pixel corresponding to each output grid point. With the imaging geometry and ephemeris data, a geo-location polynomial can be constructed from grid points that are produced by solving three equations simultaneously. And, in order to correct the local distortions induced by the geometry and terrain height, a distortion model has been incorporated in the procedure, which is a function of incidence angle and height at each pixel position. With this function, it is straightforward to calculate the pixel displacement due to distortions and then pixels are assigned to the output grid by re-sampling the displaced pixels. Most of the necessary information for the construction of polynomial model is available in the leader file and some can be derived from others. For validation, sample images of ERS-l PRI and Radarsat-l SGF have been processed by the proposed method and evaluated against ground truth acquired from 1:25,000 topography maps.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.29-35
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• 2012

In this paper, it is presented the method of image recovering which existing is only pixel processing, but suggesting method is concluding image clustering overlap degree after classfying around unit fixel to crowd pixel. Concluding overlap degree threshold value is after identifying pattern pixel and grasping geometry structure of sample pattern and deduction of deciding function. distinguishing feature space is above four dimension is reason of not visual observation of pattern structure. consideration of distribution structure is distance of center of crowd pixel, the number of each crowd pattern pixel and standard deviation. The over threshold value elimate the overlap image and the downward is recovered and established dynamic image. memory storage deduction of 20% and elevation of 15% performance is estimated in recovery of image.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.723-728
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• 2016

This study is analyzed the optical property of red tide pixel by using Landsat-7 ETM+, Landsat-8 OLI and COMS/GOCI image. In order to sample red tide pixel, Landsat-7, 8 true color image were used and obtained coordinate of red tide pixel in the true color image. Normalized water leaving radiance(nLw) and absorption coefficient were obtained from GOCI image in the same coordinate of the true color image. When red tide was not occurred the main absorption range was 412nm and 660nm but when red tide occurred it was 660nm and absorption coefficient in 412nm are drastically reduced. It made no difference of nLw spectrum between red tide pixel and non red tide pixel in nLw, but the absolute value of nLw was low than non red tide pixel, especially 660nm and 680nm wavelength sharply decrease.

• ETRI Journal
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• v.30 no.5
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• pp.747-749
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• 2008

We introduce a pixel-structured scintillator realized on a flexible polymeric substrate and demonstrate its feasibility as an X-ray converter when it is coupled to photosensitive elements. The sample was prepared by filling $Gd_2O_2S:Tb$ scintillation material into a square-pore-shape cavity array fabricated with polyethylene. For comparison, a sample with the conventional continuous geometry was also prepared. Although the pixelated geometry showed X-ray sensitivity of about 58% compared with the conventional geometry, the resolving power was improved by about 70% above a spatial frequency of 3 $mm^{-1}$. The spatial frequency at 10% of the modulation-transfer function was about 6 $mm^{-1}$.

• Aerospace Engineering and Technology
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• v.1 no.2
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• pp.66-74
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• 2002

The characteristics of the satellite image quality parameters driven by satellite imaging instrument are investigated. Since the satellite image is directly produced by the satellite imaging instrument, the satellite image quality depends on the imager performance highly. This is why the imager performance parameters are considered as an important part of the satellite image quality parameters. The imager performance parameters consist of spectral band parameters, ground sample distance(GSD) parameters, swath width parameters, imager Modulation Transfer Function (MTF), imager Signal to Noise Ratio(SNR), radiometric response characteristics parameters, pixel registration, and imager calibration.