• Title/Summary/Keyword: PSNR(Peak Signal-to-Noise Ratio)

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Quality improvement scheme of magnified image by using gradient information between adjacent pixel values (인접 픽셀 값과의 기울기 정보를 이용한 확대 영상의 화질 개선 기법)

  • Jung, Soo-Mok
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.2
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    • pp.59-67
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    • 2012
  • In this paper, an efficient interpolation scheme using gradient information between adjacent pixel values was proposed to estimate the value of interpolated pixel to have the locality which exists in real image and the characteristic of simple convex surface and simple concave surface which exist partially in the real image. PSNR(Peak Signal to Noise Ratio) was used to evaluate the performance of the proposed scheme. The PSNR values of the magnified images using the proposed scheme are greater than those of the magnified images using the previous interpolation schemes.

Image Reduction Filter for Edge Preservation in Salt and Pepper Noise Environments (Salt and Pepper 잡음 환경에서 에지 보존을 위한 영상 복원 필터)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.953-955
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    • 2016
  • Degradation is occurred in the process of the signal transmission in the image processing system due to various reasons. Degradation is noise addition in the image signal and the representative one to cause degradation is salt and pepper noise. Therefore, image restoring filter was suggested in this article to apply and process weighted value by the changes of each directional pixel upon breakdown of local mask with 8 directions in order to restore the damaged image in the environment of salt and pepper noise. In addition, peak signal to noise ratio (PSNR) was used to compare the existing method as the objective determinant standard of the improvement effect.

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Modified Median Filter using Pixel Distribution to Remove Salt and Pepper Noise (화소 분포를 이용한 Salt and Pepper 잡음 제거를 위한 변형된 메디안 필터)

  • Hong, Sang-Woo;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.274-276
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    • 2015
  • The image processing is recognized as an important field as Internet develops. The image is deteriorated in the process of obtaining, storage and transmission with various causes. Many studies have been carried out to restore the image by mainly removing the impact of salt and pepper noise added to the image. Thus, this paper proposed a modified median filter using pixel distribution in order to remove the impact of salt and pepper noise added to the image and compared it with the current methods using PSNR(peak signal to n oise ratio) as a criterion of judgment for objective judgment.

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A Study on Image Reduction Algorithm using Spatial Filter in Salt and Pepper Noise Environments (Salt and Pepper 잡음 환경에서 공간 필터를 이용한 영상 복원 알고리즘에 관한 연구)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.346-349
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    • 2017
  • Digital image processing is widely used in a variety of areas, and noise elimination is used as the preprocessing in all the image processing processes. Degradation is occurred in the image data due to multiple reasons. Degradation is to add the noise in the image signal, and salt and pepper noise is the representative one to cause degradation. Therefore, image restoration algorithm was proposed to process with histogram weight filter and median filter by the noise density of local mask to restore the damaged image in the salt and pepper noise environment, in this article. In addition, it was compared with the existing methods using peak signal to noise ratio(PSNR) as the objective determination factor of improvement effect.

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A Study on Image Restoration for Removing Mixed Noise while Considering Edge Information (에지정보를 고려한 복합잡음 제거를 위한 영상복원에 관한 연구)

  • Gao, Yinyu;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.10
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    • pp.2239-2246
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    • 2011
  • In image signal processing, image signal is corrupted by various noises and caused the degradation phenomenon. And Images often corrupted by AWGN(additive white gaussian noise) and impulse noise which called mixed noise. In this paper, the algorithm is proposed to remove mixed noise while keeping edge information. The proposed algorithm first classifies the noise type, if the classify result is AWGN, then the mean of the output after using self-adaptive weighted mean filter and median value will be the outfiltering value. And if the noise type is impulse noise, then the noise is removed by a modified nonlinear filter. Also we compare existing methods through the simulation and using PSNR(peak signal to noise ratio) as the standard of judgement of improvement effect. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms.

A Study on Modified Median Filter Algorithm for Degraded Image of Impulse Noise (임펄스 잡음에 훼손된 영상을 위한 변형된 메디안 필터 알고리즘에 관한 연구)

  • Hong, Sang-Woo;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.798-800
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    • 2014
  • In recent years, according to the improvement of Digital image technology have been recently developed most of communication technology from multimedia communication service as well as image data transmission. But In the process of storing and transmitting noise is still generated in noise and the image degrades rapidly quality of a lot of image impulse noise. To eliminate this noise, SMF, CWMF, SWMF etc. The filters have been proposed to interfere with the noise characteristics of the filter are somewhat sufficient. Therefore, in this paper, in order to remove impulse noise is proposed a modified median filter. And impulse noise removal algorithms to confirm the existed PSNR(peak signal to noise ratio) from using conventional methods were compared.

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A DCT Algorithm using shift and Additions (쉬프트와 덧셈을 이용한 DCT 알고리듬)

  • 정화자;김상중;정기현;김용득
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.6
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    • pp.773-778
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    • 1993
  • A new approach is proposed for the DCT which is widely utilized in the image processing, The approach replaces mutiplications with shift and additions, In the image restored by the proposed DCT and IDCT, no visible degration is observed and PSNR(Peak to Peak Signal to Noise Ratio) is greater than 35 dB for all cases, proving the usefulness of the proposal.

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An Image Restoration using Nonlinear Filter in Mixed Noise Environment (복합잡음 환경에서 비선형 필터를 사용한 영상복원)

  • Long, Xu;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.10
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    • pp.2447-2453
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    • 2013
  • The digital images are being degraded by noise in the process of acquisition, storage and transmission, Gaussian or impulse noise is the representative noise. Meanwhile, the image has lots of tendency to be degraded by complex noise, so various researches are being conducted for reducing these complex noise. In this paper, to remove complex noise, the algorithm processed by modified switching median filter and modified adaptive weighted filter according to the result after judging the kinds of noise is proposed. In the simulation result, excellent denoising capabilities. Furthermore, we compared proposed algorithm with existing methods for objective judgement, and PSNR(peak signal to noise ratio) is used by the criterion of judgement.

Mixed Noise Reduction Filters for CR Images (CR X선 영상의 복합잡음 감소에 관한 연구)

  • Min, Jung-Whan;Jeong, Hea-Won;Kim, Jung-Min
    • Journal of radiological science and technology
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    • v.30 no.1
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    • pp.1-6
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    • 2007
  • This study is to decrease compound noise in x-ray films. This study compared Signal to noise ratio(SNR), Peak signal to noise ratio(PSNR), Mean square error(MSE) to surface of the earth. In addition, we evaluated noise elimination effect according to the kernel size of Median filter. This experiments show that some filters are useful by finding image that is near in circle image comparing circle picture with each processed picture. In noise power value, when cutoff frequency was compared with other filters of cutoff frequency. Cutoff frequency of $2/3\pi{\sim}3/4\pi$ is good and it shows good SNR and PSNR. Therefore, it can display high filter effect. As Median Filter's Kernel size grows SNR value gets bigger, which shows better filter effect. Most pictures are distorted after filter application in medical treatment image. It is important to keep spatial resolution in most medical images. Visual estimation as well as quantitative indicators should be necessary for a better image.

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Salt and Pepper Noise Removal using Histogram (히스토그램을 이용한 Salt and Pepper 잡음 제거)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.2
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    • pp.394-400
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    • 2016
  • Currently, with the rapid development of the digital age, multimedia-related image devices become popular. However image deterioration is generated by multiple causes during the transmission process, with typical example of salt and pepper noise. When the noise of high density is added, existing methods are deteriorated in the characteristics of removal noise. After judging the noise condition to remove the salt and pepper noise, if the center pixel is the non-noise pixel, it is replaced with the original pixel. On the other hand, if it is the noise pixel, algorithm is suggested by the study, where the histogram of the corrupted image and the median filters are used. And for objective judgment, the proposed algorithm was compared with existing methods and PSNR(peak signal to noise ratio) was used as judgment standard. As the result of the simulation, The proposed algorithm shows a high PSNR of 32.57[dB] for Lena images that had been damaged of a high density salt and pepper noise(P=60%), Compared to the existing CWMF, A-TMF and AWMF there were improvements by 21.67[dB], 18.07[dB], and 20.13[dB], respectively.