• Title/Summary/Keyword: pixel value

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An Experiment on Image Restoration Applying the Cycle Generative Adversarial Network to Partial Occlusion Kompsat-3A Image

  • Won, Taeyeon;Eo, Yang Dam
    • Korean Journal of Remote Sensing
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    • v.38 no.1
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    • pp.33-43
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    • 2022
  • This study presents a method to restore an optical satellite image with distortion and occlusion due to fog, haze, and clouds to one that minimizes degradation factors by referring to the same type of peripheral image. Specifically, the time and cost of re-photographing were reduced by partially occluding a region. To maintain the original image's pixel value as much as possible and to maintain restored and unrestored area continuity, a simulation restoration technique modified with the Cycle Generative Adversarial Network (CycleGAN) method was developed. The accuracy of the simulated image was analyzed by comparing CycleGAN and histogram matching, as well as the pixel value distribution, with the original image. The results show that for Site 1 (out of three sites), the root mean square error and R2 of CycleGAN were 169.36 and 0.9917, respectively, showing lower errors than those for histogram matching (170.43 and 0.9896, respectively). Further, comparison of the mean and standard deviation values of images simulated by CycleGAN and histogram matching with the ground truth pixel values confirmed the CycleGAN methodology as being closer to the ground truth value. Even for the histogram distribution of the simulated images, CycleGAN was closer to the ground truth than histogram matching.

Controlling Brightness Compensation of Full Color LED Vision (천연색 LED 정보표시 시스템의 휘도보정 제어장치)

  • Hwang, Hyun-Hwa;Yim, Hyung-Kun;Park, Jung-Hwan;Lee, Jong-Ha
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.1291-1296
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    • 2005
  • In this paper, we prevent a display quality drop for image of characteristics brightness ununiformity depend on LED use to LED vision. It is about that method also a control system development equipped with brightness compensation function of LED vision which is done easily for LED set up of LED vision. Generally, It is calculate driving current value is attended by each brightness to brightness characteristics mathematical function establish by "Y=aX+b", When is doing brightness value for "Y", driving current value for "X", brightness compensation value by using time for "b", characteristics value for "a" ground with characteristics curve of LED. So much, First It is create brightness data of each pixel take a photograph red, green and blue of LED vision. Second It is get average error about each pixel which get average brightness value of entire. Last, It is handle a complicated for about gradationally regulation to color and brightness of image send to LED vision. Also It raise the whole average brightness value of vision adjust for "b" value to solve brightness drop problem of LED using the long time.

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Inverse Operation-based Image Steganography using Side Match for Minimum Data Damage (데이터 손상을 최소화하는 사이드 매치를 이용한 역연산 기반 이미지 스테가노그래피)

  • Che, Won-Seok;Chung, Kyung-Ho;Kim, Sung-Soo;Yun, Tae-Jin;Han, Ki-Jun
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.12
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    • pp.153-160
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    • 2014
  • The Streganography method for digital images has to insert secret data into the image without image distortion. Side match method is that size of secret data is calculated by difference of embedded pixel value and mean value of side pixels. And the secret value is embedded into the embedded pixel. Therefore, the more secret data increases, the more image distortion increases, too. In this paper, we propose the enhanced method that calculates embedded pixel value by difference of secret value and mean value of side pixels. In proposed method, more secret data is embedded and image distortion has to decreases.

Image Restoration Algorithm using Weighted Switching Filter for Remove Random-Valued Impulse Noise (랜덤 임펄스 잡음을 제거하기 위한 가중치 스위칭 필터를 이용한 영상 복원 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.5
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    • pp.609-615
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    • 2020
  • In the modern society, the use of digital equipment is increasing along with the 4th industrial revolution, and the importance of image and signal processing is increasing. At the same time, research on noise reduction is being actively conducted. In this paper, we propose a switching filter algorithm for random-valued impulse noise cancellation. The proposed algorithm obtains the threshold value by determining the noise level present in the image, and threshold value is compared with the difference between the input pixel value and the reference value, and is used in the weight switching process of the filter. The final output of the filter is estimated by applying a pixel weight and a modified weight median filter according to the switching, and obtains a final output by comparing the estimated value with the input pixel value. To evaluate the performance of the proposed algorithm, we compared it with the existing methods using simulation and PSNR.

Detection and segmentation of circular shaped objects using spatial information on boundary neighborhood (테두리 주위의 공간정보를 이용한 둥근 물체의 검색 및 분할)

  • 성효경;김성완;최흥문
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.6
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    • pp.30-37
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    • 1997
  • We present an efficient technique, bidirectioanl inertial maximum cost search technique, for th edetection and segmentation of circular shaped objects using the spatial information around the neighborhood of the boundary candidates. This technique searches boundary candidates using local pixdl information such as pixel value and its direction. And then to exclude pseudo-boundary caused by shadows or noises, the local contrast is defined between the clique of the boundary candidates and the cliques of the background. In order to effectively segment circular shaped boundary, the technique also uses the curvature based on trigonometirc function which determines circular shaped boundary segments. Since the proposed technique is applied to the pixel cliques instead of a pixel itself, it is proposed method can easily find out circular boundaries form iamges of the PCB containing circular shaped parts and the trees with round fruits compared to boundary detection by using the pixel information and the laplacian curvature.

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Information Hiding Method based on Interpolation using Max Difference of RGB Pixel for Color Images (컬러 영상의 RGB 화소 최대차분 기반 보간법을 이용한 정보은닉 기법)

  • Lee, Joon-Ho;Kim, Pyung-Han;Jung, Ki-Hyun;Yoo, Kee-Young
    • Journal of Korea Multimedia Society
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    • v.20 no.4
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    • pp.629-639
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    • 2017
  • Interpolation based information hiding methods are widely used to get information security. Conventional interpolation methods use the neighboring pixel value and simple calculation like average to embed secret bit stream into the image. But these information hiding methods are not appropriate to color images like military images because the characteristics of military images are not considered and these methods are restricted in grayscale images. In this paper, the new information hiding method based on interpolation using RGB pixel values of color image is proposed and the effectiveness is analyzed through experiments.

Enhancement of Color Images with Blue Sky Using Different Method for Sky and Non-Sky Regions

  • Ghimire, Deepak;Pant, Suresh Raj;Lee, Joonwhoan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.05a
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    • pp.215-218
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    • 2013
  • In this paper, we proposed a method for enhancement of color images with sky regions. The input image is converted into HSV space and then sky and non-sky regions are separated. For sky region, saturation enhancement is performed for each pixel based on the enhancement factor calculated from the average saturation of its local neighborhood. On the other hand, for the non-sky region, the enhancement is applied only on the luminance value (V) component of the HSV color image, which is performed in two steps. The luminance enhancement, which is also called as dynamic range compression, is carried out using nonlinear transfer function. Again, each pixel is further enhanced for the adjustment of the image contrast depending upon the center pixel and its neighborhood pixel values. At last, the original H and V component image and enhanced S component image for the sky region, and original H and S component image and enhanced V component image for the non-sky region are converted back to RGB image.

Research of Phase Correlation Method for Identifying Quantitative Similarity in Adjacent Real-time Streaming Frame

  • Cho, Yongjin;Yun, Yeji;Lee, Kyou-seung;Oh, Jong-woo;Lee, DongHoon
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2017.04a
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    • pp.157-157
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    • 2017
  • To minimize the damage by wild birds and acquire the benefits such as protection against weeds and maintenance of water content in soil, the mulching black color vinyl after seeding should be carried out. Non-contact and non-destructive methods that can continuously determine the locations are necessary. In this study, a crop position detection method was studied that uses infrared thermal image sensor to determine the cotyledon position under vinyl mulch. The moving system for acquiring image arrays has been developed for continuously detecting crop locations under plastic mulching on the field. A sliding mechanical device was developed to move the sensor, which were arranged in the form of a linear array, perpendicular to the array using a micro-controller integrated with a stepping motor. The experiments were conducted while moving 4.00 cm/s speed of the IR sensor by the rotational speed of the stepping motor based on a digital pulse width modulation signal from the micro-controller. The acquired images were calibrated with the spatial image correlation. The collected data were processed using moving averaging on interpolation to determine the frame where the variance was the smallest in resolution units of 1.02 cm. Non-linear integral interpolation was one of method for analyzing the frequency using the normalization image and then arbitrarily increasing the limited data value of $16{\times}4pixels$ in one frame. It was a method to relatively reduce the size of overlapping pixels by arbitrarily increasing the limited data value. The splitted frames into 0.1 units instead of 1 pixel can propose more than 10 times more accurate and original method than the existing correction method. The non-integral calibration method was conducted by applying the subdivision method to the pixels to find the optimal correction resolution based on the first reversed frequency. In order to find a correct resolution, the expected location of the first crop was indicated on near pixel 4 in the inversion frequency. For the most optimized resolution, the pixel was divided by 0.4 pixel instead of one pixel to find out where the lowest frequency exists.

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Evaluating the Contribution of Spectral Features to Image Classification Using Class Separability

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.36 no.1
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    • pp.55-65
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    • 2020
  • Image classification needs the spectral similarity comparison between spectral features of each pixel and the representative spectral features of each class. The spectral similarity is obtained by computing the spectral feature vector distance between the pixel and the class. Each spectral feature contributes differently in the image classification depending on the class separability of the spectral feature, which is computed using a suitable vector distance measure such as the Bhattacharyya distance. We propose a method to determine the weight value of each spectral feature in the computation of feature vector distance for the similarity measurement. The weight value is determined by the ratio between each feature separability value to the total separability values of all the spectral features. We created ten spectral features consisting of seven bands of Landsat-8 OLI image and three indices, NDVI, NDWI and NDBI. For three experimental test sites, we obtained the overall accuracies between 95.0% and 97.5% and the kappa coefficients between 90.43% and 94.47%.

The Cut Detection System using Sum of Square Difference of Color between frames of Video Image Data (동영상데이터의 프레임간 색상차의 자승합을 이용한 컷 검출시스템)

  • 김병철;정창렬;고진광
    • Journal of Internet Computing and Services
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    • v.3 no.5
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    • pp.51-62
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    • 2002
  • The development of computer technology and the advancement of the technology of information and communications spread the technology of multimedia and increased the use of multimedia data with large capacity, Users can grasp the overall video data and they are able to play wanted video back. To grasp the overall video data it is necessary to offer the list of summarized video data information, In order to search video efficiently on index process of video data is essential and it is also indispensable skill, Therefore, this thesis suggested the effective method about the cut detection of frames which will become a basis of an index based on contents of video image data. This suggested method was detected as the unchanging pixel color intelligence value, classified into diagonal direction. Pixel value of color detected in each frame of video data is stored as A(i, j) matrix-i is the number of frames. j is an image height of frame. By using the stored pixel value as the method of sum of squared difference of color two frames I calculated a specified value difference between frames and detected cut quickly and exactly in case it is bigger than threshold value set in advance, To carry out on experiment on the cut detection of frames comprehensively, I experimented on many kinds of video. analyzing and comparing efficiency of the cut detection system.

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