• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2015년도 춘계학술대회
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• pp.932-935
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• 2015

Recently, the image system is utilized in several fields due to the development of multimedia technology. However, the noise occurs according to various causes in the process of image data processing. The noises added to the image include several types according to the cause and shape, and the salt and pepper noise is one of the typical noise types. Thus, this paper proposed the median filter algorithm using the estimated mask in order to remove the salt and pepper noise effectively and also compared this algorithm with the current methods using PSNR(peak signal to noise ratio) as a criterion of judgment.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제14권5호
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• pp.1251-1256
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• 2010

In the transmitting process of image signal processing system, there are several different causes of degradation that have been occuring. The main cause of degradation is attributed to the noise. The most representive method of removing noise of image, which is caused by impulse noise environment, is using the SM filter. At edge, the filter has a special feature which has a tendency to decrease. As a result, we proposed a nonlinear filter using the form of mask and the probability of the impulse noise to restore the image considering edge quality in the impulse noise environment. And through the simulation, we compared with the existings and capabilities.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제11권7호
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• pp.1373-1379
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• 2007

A modified adaptive switching median filter for impulse noise removal, which has the noise detection step and the noise filtering step, is proposed in this paper. In the noise detection step, we use the detection threshold which is earned by calculating the intensity differences between pixels nearby with each other in localized window, to determine whether the pixels in the image are noise or not. Then in the noise filtering step, we will only remove the corrupted pixels and remain the good pixels. By the noise detection result, we can easily get the local noise density of the image, and use it to consider the filtering mask size and the times of filtering iteration according to different localized noise corruptions. For Setting the simulation result, we compared the proposed method to conventional median filters with several test images corrupted by various impulse noise densities. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, the simulation results demonstrate that the proposed method shows better results than other median-based type filters.

• Journal of the Korea Society of Computer and Information
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• 제15권11호
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• pp.41-45
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• 2010

Image processing techniques are fundamental in human vision-based image information processing. There have been widely studied areas such as image transformation, image enhancement, image restoration, and image compression. One of research subgoals in those areas is enhancing image information for the correct information retrieval. As a fundamental task for the image recognition and interpretation, image enhancement includes noise filtering techniques. Conventional filtering algorithms may have high noise removal rate but usually have difficulty in conserving boundary information. As a result, they often use additional image processing algorithms in compensation for the tradeoff of more CPU time and higher possibility of information loss. In this paper, we propose a Fuzzy Mask Filtering algorithm that has high noise removal rate but lesser problems in above-mentioned side-effects. Our algorithm firstly decides a threshold based on fuzzy logic with information from masks. Then it decides the output pixel value by that threshold. In a designed experiment that has random impulse noise and salt pepper noise, the proposed algorithm was more effective in noise removal without information loss.

• IEMEK Journal of Embedded Systems and Applications
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• 제12권6호
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• pp.395-403
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• 2017

Image processing for object detection and identification has been studied for supply chain management application with various approaches. Among them, feature pointed detection algorithm is used to track an object or to recognize a position in automated supply chain systems and a depth image based feature point detection is recently highlighted in the application. The result of feature point detection is easily influenced by image noise. Also, the depth image has noise itself and it also affects to the accuracy of the detection results. In order to solve these problems, we propose a novel hybrid filtering mechanism for depth image based feature point detection, it shows better performance compared with conventional hybrid filtering mechanism.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1711-1714
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• 2003

The noise in an image degrades image quality and deteriorates coding efficiency of compression. Recently, various edge-preserving noise filtering methods based on the nonstationary image model have been proposed to overcome this problem. In most conventional nonstationary image models, however, pixels are assumed to be uncorrelated to each other In order not to increase the computational burden too much. As a result, some detailed information is lost in the filtered results. In this paper, we propose a computationally feasible adaptive noise smoothing algorithm which considers the nonstationary correlation characteristics of images. We assume that an image has a nonstationary mean and can be segmented into subimages which have individually different stationary correlations. Taking advantage of the special structure of the covariance matrix that results from the proposed image model, we derive a computationally efficient FFT-based adaptive linear minimum mean square error filter. The justification for the proposed image model is presented and the effectiveness of the proposed algorithm is demonstrated experimentally.

• Journal of Radiation Protection and Research
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• 제24권3호
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• pp.161-170
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• 1999

System performances in terms of image quality between an amorphous silicon DR system and a conventional film-screen system were evaluated. Various aspects of image quality MTF (modulation transfer function), NPS (noise power spectrum), SNR(signal-to-noise ratio) and contrast were measured and calculated. The MTF of the DR system was comparable to the film-screen systems. The noise was mainly dominated by the quantum mottle in both systems and the electronic noise was found in the DR system. The contrast of the DR system was better than the film-screen systems by virtue of high sensitivity and image processing. Compared to the film-screen systems in general radiography, the DR system had similar resolution and showed better contrast with the same exposure condition after contrast manipulation. The results of this study provide some useful information about the performance of the DR system in connection with medical applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제27권1호
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• pp.47-53
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• 2023

Devices such as X-Ray, CT, MRI, scanners, etc. can generate S&P noise from several sources during the image acquisition process. Since S&P noise appearing in the image degrades the image quality, it is essential to use noise reduction technology in the image processing process. Various methods have already been proposed in research on S&P noise removal, but all of them have a problem of generating residual noise in an environment with high noise density. Therefore, this paper proposes a filtering algorithm based on a three-dimensional plane equation by setting the grayscale value of the image as a new axis. The proposed algorithm subdivides the local mask to design the three closest non-noisy pixels as effective pixels, and applies cosine similarity to a region with a plurality of pixels. In addition, even when the input pixel cannot form a plane, it is classified as an exception pixel to achieve excellent restoration without residual noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.253-255
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• 2022

Thanks to the 4th industrial revolution and the development of various communication media, technologies such as artificial intelligence and automation are being grafted into industrial sites in various fields, and accordingly, the importance of data processing is increasing. Image noise removal is a pre-processing process for image processing, and is mainly used in fields requiring high-level image processing technology. Various studies have been conducted to remove noise, but various problems arise in the process of noise removal, such as image detail preservation, texture restoration, and noise removal in a special area. In this paper, we propose a switching mask filter based on the noise intensity to preserve the detailed image information during the impulse noise removal process. The proposed filter algorithm obtains the final output by switching to the extended mask when it is determined that the density is higher than the reference value when noise is determined in the area designated as the filtering mask. Simulation was conducted to evaluate the performance of the proposed algorithm, and the performance was analyzed compared to the existing method.

• Journal of the Korean Institute of Telematics and Electronics
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• 제24권4호
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• pp.713-718
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• 1987

In this paper, an iterative restoration algorithm from power spectral density with 1 bit sign information of real part of two dimensional Fourier transform of image corrupted by additive white Gaussian noise is proposed. This method is a modified version of image reconstruction algorithm from power spectral density. From the results of computer simulation with original 32 gray level imgae of 64x64 pixels, we can find that restorated image after each iteration converge to original image very fast, and SNR gain be at least 8[dB] after 10th iteration for corrupted image with additive white Gaussian noise.