• Title/Summary/Keyword: Noise Removal

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A Simple Multi-rate Parallel Interference Canceller for the IMT-2000 3GPP System (IMT-2000 3GPP 시스템을 위한 간단한 다중 전송률 병렬형 간섭제거기)

  • Kim, Jin-Kyeom;Oh, Seong-Keun;Sunwoo, Myung-Hoon
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.38 no.12
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    • pp.10-19
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    • 2001
  • In this paper, we propose an effective but simple multi-rate parallel interference canceller(PIC) for the international mobile telecommunications-2000(IMT-2000) 3rd generation partnership project (3GPP) system. For effective multi-rate processing, we define the basic block as one symbol period of the dedicated physical control channel(DPCCH) having the lowest data rate and common to all users. Then, decision and interference cancellation are performed at every basic block. For an asynchronous channel, we propose an advance removal scheme that removes in advance multiple access interference(MAI) due to the next blockof other users with shorter delay. Introducing a pipeline structure at a sample base, we can implement efficiently the PIC using the advance removal scheme with a minimum hardware and no extra computations. Through computer simulations, we analyze the bit error rate(BER) performance of the proposed PIC with respect to signal-to-noise ratio(SNR) and the number of users.

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Rear Vehicle Detection Method in Harsh Environment Using Improved Image Information (개선된 영상 정보를 이용한 가혹한 환경에서의 후방 차량 감지 방법)

  • Jeong, Jin-Seong;Kim, Hyun-Tae;Jang, Young-Min;Cho, Sang-Bok
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.1
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    • pp.96-110
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    • 2017
  • Most of vehicle detection studies using the existing general lens or wide-angle lens have a blind spot in the rear detection situation, the image is vulnerable to noise and a variety of external environments. In this paper, we propose a method that is detection in harsh external environment with noise, blind spots, etc. First, using a fish-eye lens will help minimize blind spots compared to the wide-angle lens. When angle of the lens is growing because nonlinear radial distortion also increase, calibration was used after initializing and optimizing the distortion constant in order to ensure accuracy. In addition, the original image was analyzed along with calibration to remove fog and calibrate brightness and thereby enable detection even when visibility is obstructed due to light and dark adaptations from foggy situations or sudden changes in illumination. Fog removal generally takes a considerably significant amount of time to calculate. Thus in order to reduce the calculation time, remove the fog used the major fog removal algorithm Dark Channel Prior. While Gamma Correction was used to calibrate brightness, a brightness and contrast evaluation was conducted on the image in order to determine the Gamma Value needed for correction. The evaluation used only a part instead of the entirety of the image in order to reduce the time allotted to calculation. When the brightness and contrast values were calculated, those values were used to decided Gamma value and to correct the entire image. The brightness correction and fog removal were processed in parallel, and the images were registered as a single image to minimize the calculation time needed for all the processes. Then the feature extraction method HOG was used to detect the vehicle in the corrected image. As a result, it took 0.064 seconds per frame to detect the vehicle using image correction as proposed herein, which showed a 7.5% improvement in detection rate compared to the existing vehicle detection method.

A Real-time Correction of the Underestimation Noise for GK2A Daily NDVI (GK2A 일단위 NDVI의 과소추정 노이즈 실시간 보정)

  • Lee, Soo-Jin;Youn, Youjeong;Sohn, Eunha;Kim, Mija;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1301-1314
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    • 2022
  • Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.

The Edge Detection of Image using the quantization FCNN with the variable template (가변 템플릿의 양자화 FCNN을 이용한 영상 에지 검출)

  • Choi, Seon-Kon;Byun, Oh-Sung;Lee, Cheul-Hee;Moon, Sung-Ryong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.11
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    • pp.144-151
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    • 1998
  • In this paper, it is applied the analysis properties of mathematical morphology in order to process MIN/MAX operation on the basis of combination of predefined and weighted structuring element to FCNN having the structure of CNN combined with fuzzy logic between template and input/output. In this paper, as the fuzzy estimator is applied to the image including noise, thus it could be found the noise removal as well as the edge detection in the process of computer simulation. We could analyze and compare the results of edge detection using FCNN, CNN and median filter to which the erosion operation of morphology is applied. This paper could apply the static template and the variable template to FCNN using the quantization fuzzy function, in result we could confirm that the performance of FCNN got to improve in the process of computer simulation.

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Halftone Noise Removal in Scanned Images using HOG based Adaptive Smoothing Filter (HOG 기반의 적응적 평활화를 이용한 스캔된 영상의 하프톤 잡음 제거)

  • Hur, Kyu-Sung;Baek, Yeul-Min;Kim, Whoi-Yul
    • Journal of Broadcast Engineering
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    • v.17 no.2
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    • pp.316-324
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    • 2012
  • In this paper, a novel descreening method using HOG(histogram of gradient)-based adaptive smoothing filter is proposed. Conventional edge-oriented smoothing methods does not provide enough smoothing to the halftone image due to the edge-like characteristic of the halftone noise. Moreover, clustered-dot halftoning method, which is commonly used in printing tends to create Moire pattern because of the intereference in color channels. Therefore, the proposed method uses HOG to distinguish edges and the amount of smoothing to be performed on the halftone image is then calculated according to the magnitude of the HOG in the edge and edge normal orientation. The proposed method was tested on various scanned halftone materials, and the results show that it effectively removes halftone noises as well as Moire pattern while preserving image details.

Fault Detection Algorithm of Charge-discharge System of Hybrid Electric Vehicle Using SVDD (SVDD기법을 이용한 하이브리드 전기자동차 충-방전시스템의 고장검출 알고리듬)

  • Na, Sang-Gun;Yang, In-Beom;Heo, Hoon
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.21 no.11
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    • pp.997-1004
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    • 2011
  • A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.

Development of Machining System for Gouging of Nozzle Welded Area (압력용기 노즐 용접부 절삭 가우징 장치 개발)

  • Son, Seong-Min
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.10
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    • pp.2596-2601
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    • 2009
  • Gouging is defined as the removal of weld metal and base metal from the opposite of a partially welded joint to facilitate complete joint penetration. Since the work by current method needs skillful welding and grinding, there is a limit on the increase of operation efficiency. Noise and dust from the weld gouging also deteriorate the work place and cause environmental problems. In this study, the gouging work by cutting method is proposed to overcome the defects from weld gouging such as low productivity, severe noise, dense dust, and so on. The developed cutting gouging system removes material as much as $13,565mm^3/min$, and enlarge the labor productivity as three times compared to that by weld gouging method.

X-ray Image Denoising Agorithm Using Bilateral Weight (양방향 가중치를 이용한 x선 영상 잡음 제거 알고리즘)

  • Shin, Soo-Yeon;Suh, Jae-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.1
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    • pp.137-143
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    • 2017
  • X-ray image is a widely used to medical examination, airport security and cargo inspection. However, X-ray images contain many visual noise, which interrupt image analysis. Consequently, it is primary importance to reduce noises of X-ray image. In this paper, we present a improved denoise technique for x-ray image using pixel value and range weights. First, we denoise a x-ray image using bilateral filter. Next, we detect a edge region of the original x-ray image. If a denoised pixel belongs to the edge region, we calculate weighting values of original x-ray image and denoised x-ray image in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Finally, the pixel value having minimum cost is determined as the pixel value of the denoised x-ray image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.

AWGN Removal using Edge Information of Local Mask (국부 마스크의 에지 정보를 이용한 AWGN 제거)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • 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.

A New Semi-Random Imterleaver Algorithm for the Noise Removal in Image Communication (영상통신에서 잡음 제거를 위한 새로운 세미 랜덤 인터리버 알고리즘)

  • Hong, Sung-Won;Park, Jin-Soo
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.8
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    • pp.2473-2483
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    • 2000
  • In this paper, The turbo code is used to effectively remove noise which is generated on the image communication channel. Turbo code had excellent decoding performance. However, it had limitations for real time communication because of the system complexity and time delay in decoding procedure. To overcome this problem, this paper proposed a new SRI(Semi Random Interleaved algorithm, which decrease the time delay, when the image data, which reduced the interleaver size of turbo code encoder and decoder, transmitted. The SRI algorithm was composed of 0.5 interleaver size from input frame sequence. When the data inputs in interleaver, the data recorded by row such as block interleaver. But, When the data read in interleaver, the data was read by randomly and the next data located by the just address simultaneously. Therefore, the SRI reduced half-complexity when it was compared with pre-existing method such as block, helical, random interleaver. The image data could be the real time processing when the SRI applied to turbo code.

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