• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.922-934
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• 1993

In this paper, statistical properties of the spatiotemporal center weighted median(CWM) filter for image sequences are investigated. It is statistically shown that the CWM filter preserves image structures under motion at the expense of noise suppression. To improve the CWM filter, a filter which can be effectively used in image sequence processing, the adaptive directional center weighted median filter (ADCWM), is proposed. This filter utilizes a multistage filtering structure based on adaptive symmetric order statistic(ASOS) operators which produce a pall of order statistics symmetric about the median. The ASOS's are selected by using adaptive parameters adjusted by local image statistics. It is shown experimentally that the proposed filter can preserve image structures while attenuating noise without the use of motion estimation.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2328-2333
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• 2020

The filter technique was applied to noise images, as noise is the significant factor that cause poor image quality due to lower photon counting. The purpose of this study is to confirm that image quality can be improved using the median modified Wiener filter (MMWF) technique; this is achieved via a National Electrical Manufacturers Association International Electrotechnical Commission body phantom with four large spheres that are filled with the ^99mTc radioisotope when evaluating the image quality. Conventional filters such as Wiener, Gaussian, and median filters were designed, and signal to noise ratio, coefficient of variation, and contrast to noise ratio were used as the evaluation parameters. The improvement in the image quality was in the following order, from the least to the highest improvement, in all cases: Wiener filter, Gaussian filter, median filter, and the MMWF technique. The results show that the image quality was improved from 20.6 to 65.5%, 7.4-40.3%, and 12.7-44.7% for the SNR, COV, and CNR values, respectively, when using the MMWF technique, compared with the use of conventional filters. In conclusion, our results demonstrated that the MMWF technique is useful for reducing the noise distribution in gamma camera images.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.293-296
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• 2007

In this paper, we propose the systolic array architecture for the vector median filter. In the color image processing, the vector signal (i.e. the color) consists of three elements, red, green and blue. The vector median filter is very effective to utilize the correlation among red, green and blue elements. The computational complexity of the proposed architecture for computing the vector median of N vector signals is (N+2) clock periods compared to the (3N+1) clock periods in the previous method. In addition to, the input vector signals can be loaded in serial in the proposed architecture. In the previous method, N input vector signals should be loaded to the vector median filter in parallel at the first clock. The proposed architecture is implemented with FPGA.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.376-381
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• 2009

The image data compression, recognition, restoration, etc. are parts of the digital image processing technology. In the process by various devices, noises would be made. Because the noise could damage the image, we use the image filter to preserve the original image from the noise. The image filter used in digital image process basically has a two-dimensional structure. There an two methods of creating the filter - One is reiterating one dimension and the other is using an indivisible two-dimension image filter. The image filter is being widely used along with one-dimension filter according to each noise, and various median filters are being used to remove the impulse noise. In this paper, I suggested a powerful modified median filter, and compared with conventional filters for objective verification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.883-885
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• 2013

Image restoration refers to removing different kinds of noise added to image, and to reducing effect of noise upon image. For image restoration, some methods such as mean filter, median filter and weighted filter were proposed, but the existing methods have poor denoising and edge-reserved performance. Therefore, in this paper modified median filter algorithm was proposed that enlarges mask size according to median value of mask in order to remove noise efficiently. And, it was compared by simulation to the existing methods, and MSE(mean squared error) was used on a criterion of evaluation.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.207-213
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• 2014

In this paper, we propose a modified median filter for impulse noise reduction. The proposed method based on multi-step finds noisy pixels from the corrupted image and applies filtering on the noisy pixels. Neighbor pixels for filtering are filtered by linear filter which adjusts filtering direction according to an edge. Thus, our proposed method not only preserves edge, but also reduces noise in uniform region. Experimental results show that our proposed method has better quality than those by existing modified median filtering method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.285-294
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• 2004

Median Filters in the Signal Processing have been most widely used and have demonstrated the most strongest effects. This paper proposes the Adaptive Median Filters by using noise detection. The basic algorithm of the proposed filters is to determine whether noise or not by the each noise judgement standards, and then take the Median Filter if it satisfies the conditions as a result of judgement and returns to the original image(No Filters) if not. This paper presented Noise Detection by Local Variance and Local Central Variance for noise judgement, compared and analyzed the features and performance of existing [5]∼[10] Filters. Filter improved on the result of executing the existing filters at the same condition and showed the effects over that when it was judged with naked eyes. Accordingly, the Adaptive Median Filters by Local Variance and Local Central Variance was proven to have reinforced edge preservation ability and have the strong features for removing the Impulse Noise of the Median Filter.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.104-115
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• 2005

Median filters in the signal processing have been most widely used and have demonstrated the strongest effects. This paper proposes the adaptive median filters with noise detection. The proposed basic algorithm of the filters is to judge whether or not the noises exist on the ground of The Noise Judgment Standards. Just in case the existence of the noises is verified by the algorithm, it takes the median filter. In order to judge the existence of the noises by the algorithm, this paper introduced the noise detection method by local central variance. As a result of comparing and analyzing the features and performance of the proposed filters and the existing [5]-[10] filters on the same conditions, it was verified that the former proved to be better than the latter, Observed even by naked eyes, it was similar, too. Accordingly, it's proved that the adaptive median filters by local central variance are useful in removing the impulse noise of the median filter and reinforce the edge preservation ability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.634-642
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• 2020

With the proliferation of Internet of Things (IoT) devices, using the Linux operating system in various architectures has increased. Also, security threats against Linux-based IoT devices are increasing, and malware variants based on existing malware are constantly appearing. In this paper, we propose a system where the binary data of a visualized Executable and Linkable Format (ELF) file is applied to Local Binary Pattern (LBP) image processing techniques and a median filter to classify malware in a Convolutional Neural Network (CNN). As a result, the original image showed the highest accuracy and F1-score at 98.77%, and reproducibility also showed the highest score at 98.55%. For the median filter, the highest precision was 99.19%, and the lowest false positive rate was 0.008%. Using the LBP technique confirmed that the overall result was lower than putting the original ELF file through the median filter. When the results of putting the original file through image processing techniques were classified by majority, it was confirmed that the accuracy, precision, F1-score, and false positive rate were better than putting the original file through the median filter. In the future, the proposed system will be used to classify malware families or add other image processing techniques to improve the accuracy of majority vote classification. Or maybe we mean "the use of Linux O/S distributions for various architectures has increased" instead? If not, please rephrase as intended.

• Geophysics and Geophysical Exploration
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• v.15 no.4
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• pp.199-208
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• 2012

High-amplitude swell noises (HASN) are very difficult to eliminate from the marine seismic data. In this paper, we applied F-X filter and median filter in order to suppress HASN. Test data have been acquired on the northern offshore of the South Shetland Islands in December, 2010. Parts of data have been contaminated by HASN caused by bad weather during the cruise. We applied F-X filter and median filter to test data with HASN. After F-X filtering, most of non-coherent noises and small-amplitude swell noises are eliminated effectively but HASN are still remained significantly. With median filter, HASN was suppressed better than F-X filter, however some of non-coherent noises are still remains. We applied a cascade of two filters and results show HASN and non-coherent noises are suppressed effectively. After the cascade of two filtering, it is possible to define reflection layers clearly on the velocity spectrum and to produce better stacked section with a good signal-to-noise ratio.