• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.474-486
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• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.283-296
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• 2005

Nowadays, Global Navigation Satellite System(GNSS) which is the new concept of positioning system has been developed because of satisfaction human's intelligent desire and rapid science development. GNSS which is represented by GPS provides 3-Dimension positioning information not expensively in whenever, wherever. The industry of positioning information has extending civil market widely as well as military market. So GNSS is running the role of society infra structure including car and airborne navigation, civil engineering, GIS resource, telematics and LBS, and so on. As USA removes the SA(Selective Availability), GPS has monopolizing the market and other countries have been depended on GPS, absolutely. In this paper, the author developed the software for analysis of influence using next generation, Galileo system. The local analysis was performed according to positioning mode. And GPS/Galileo combined system can implement positioning in the worst mask environment like urban cannon.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1383-1388
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• 2016

Although image signal processing is used in many fields, degradation takes place in the process of transmitting image data by several causes. CWMF, A-TMF, and AWMF are the typical methods to eliminate noises from image data damaged under salt and pepper noise environment. However, those filters are not effective for noise rejection under highly dense noise environment. In this respect, the present study proposed an algorithm to remove in salt and pepper noise. In case the center pixel is determined to be non-noise, it is replaced with original pixel. In case the center pixel is noise, it segments local mask into 4 directions and uses linear interpolation to estimate original pixel. And then it applies spatial weight to the estimated pixel. The proposed algorithm shows a high PSNR of 24.56[dB] for House images that had been damaged of salt and pepper noise(P = 50%), compared to the existing CWMF, A-TMF and AWMF there were improvements by 16.46[dB], 12.28[dB], and 12.32[dB], respectively.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1347-1359
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• 2005

We propose an efficient block classification of the document images using the second-order statistical texture features computed from spatial gray level dependence matrix (SGLDM). We studied on the techniques that will improve the block speed of the segmentation and feature extraction speed and the accuracy of the detailed classification. In order to speedup the block segmentation, we binarize the gray level image and then segmented by applying smoothing method instead of using texture features of gray level images. We extracted seven texture features from the SGLDM of the gray image blocks and we applied these normalized features to the BP (backpropagation) neural network, and classified the segmented blocks into the six detailed block categories of small font, medium font, large font, graphic, table, and photo blocks. Unlike the conventional texture classification of the gray level image in aerial terrain photos, we improve the classification speed by a single application of the texture discrimination mask, the size of which Is the same as that of each block already segmented in obtaining the SGLDM.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.130-136
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• 2017

Recently, as demand of video processor unit rapidly increases, excellent quality of the video has been required. However, generally, video data occurs the quick flame of video due to various external causes in process of acquisition, treatment, and transmission, and major cause of the quick flame of the video is known as the noise. There are various kinds of noise, which are added to the video, AWGN is a typical one. Thus, this thesis suggested algorithm that treats in three methods by scale of the edge through using edge information of local masks. In case that edge pixel is big, it applied spatial weighting according to equation of straight line about direction of edge pixel. In case that edge pixel is middle, it suggested algorithm with spatial weighting filter and average filter, and for the smooth territory, it suggested algorithm that treats with average filter.

• Journal of Radiation Protection and Research
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• v.29 no.4
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• pp.257-261
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• 2004

A coded-aperture gamma camera was developed to increase the sensitivity of a pin hole camera made with a pixellated CsI(Tl) scintillator and a position-sensitive photomultiplier tube. The modified round-hole uniformly redundant array of pixel size $13{\times}11$ was chosen as a coded mask considering the detector spatial resolution. The performance of the coded-aperture camera was compared with the pin hole camera using various forms of Tc-99m source to see the improvement of signal-to-noise ratio or the improvement of the sensitivity. The image quality is much improved despite of a slight degradation of the spatial resolution. Though the camera and the test were made for low energy case, but the concept of the coded-aperture gamma camera could be effectively used for the radioactive environmental monitoring and other applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.237-243
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• 2015

In recent image processing, active researches have been made along with rapid development in digital times. However, it is know that the image degradation occurs due to various external factors in the processes of image data processing, transmission and storage, and the main reason of image degradation is due to the noise. Typical methods to remove the noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter) and these methods have a little bit lacking noise reduction characteristics in mixed noise environments. Therefore, in order to remove the mixed noise, image restoration filter processing algorithm was suggested in this paper which processes by applying the median value of the mask and space weighted value after noise judgment. And for the objective judgment, it was compared with existing methods and PSNR(peak signal to noise ratio) was used as a judgment standard.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.213-215
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• 2021

With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. In particular, a system based on a digital image may cause a malfunction due to noise in the image due to a sensor defect or a communication environment problem. Therefore, research on image processing has been continued as a pre-processing process, and an effective noise reduction technique is required depending on the type of noise and the characteristics of the image. In this paper, we propose a modified spatial weight filter to protect edge components in the impulse noise reduction process. The proposed algorithm divides the filtering mask into four regions and calculates the standard deviation of each region. The final output was filtered by applying a spatial weight to the region with the lowest standard deviation value. Simulation was conducted to evaluate the performance of the proposed algorithm, and it showed superior impulse noise reduction performance compared to the existing method.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.733-739
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• 2016

Insolation is an major indicator variable that can serve as an energy source in earth system. It is important to monitor insolation content using remote sensing to evaluate the potential of solar energy. In this study, we performed sensitivity analysis of observed frequency on daily composite insolation over the Korean peninsula. We estimated INS through the channel data of Communication, Ocean and Meteorological Satellite (COMS) and Cloud Mask which have temporal resolution of 1 and 3 hours. We performed Hemispherical Integration by spatial resolution for meaning whole sky. And we performed daily composite insolation. And then we compared the accuracy of estimated COMS insolation data with pyranometer data from 37 points. As a result, there was no great sensitivity in the daily composite INS by observed frequency of satellite that accuracy of the calculated insolation at 1 hour interval was $28.6401W/m^2$ and 3 hours interval was $30.4960W/m^2$. However, there was a great difference in the space distribution of two other INS data by observed frequency of clouds. So, we performed sensitivity analysis with observed frequency of clouds and distinction between the two other INS data. Consequently, there was showed sensitivity up to $19.4392W/m^2$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3823-3840
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• 2020

Recently, auto-encoder has emerged as the most popular method in convolutional neural network (CNN) based image compression and has achieved impressive performance. In the traditional auto-encoder based image compression model, the encoder simply sends the features of last layer to the decoder, which cannot allocate bits over different spatial regions in an efficient way. Besides, these methods do not fully exploit the contextual information under different receptive fields for better reconstruction performance. In this paper, to solve these issues, a novel auto-encoder model is designed for image compression, which can effectively transmit the hierarchical features of the encoder to the decoder. Specifically, we first propose an adaptive bit-allocation strategy, which can adaptively select an importance channel. Then, we conduct the multiply operation on the generated importance mask and the features of the last layer in our proposed encoder to achieve efficient bit allocation. Moreover, we present an additional novel perceptual loss function for more accurate image details. Extensive experiments demonstrated that the proposed model can achieve significant superiority compared with JPEG and JPEG2000 both in both subjective and objective quality. Besides, our model shows better performance than the state-of-the-art convolutional neural network (CNN)-based image compression methods in terms of PSNR.