• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.253-255
• /
• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.397-400
• /
• 2016

In digital images, the addition due to noise occurs in the process of obtaining, saving, and transmitting. For examples of noise, there are salt and pepper noise, Gaussian noise, and composition noise where various noises are mixed. Existing filters have insufficient noise removal characteristics because it uses single filters in composite noise environment. Therefore the study suggested a switching filter that processes with special weighted value and median filter according to local mask salt and pepper noise density when central pixel is damaged by salt and pepper noise, and processes by applying weighted values differently according to standard deviation of local mask when damaged by Gaussian noise.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.27 no.1
• /
• pp.54-61
• /
• 2023

With the development of IoT technologies and artificial intelligent, diverse digital image equipments are being used in industrial sites. Because image data can be easily damaged by noise while it's obtained with a camera or a sensor and the damaged image has a bad effect on the process of image processing, noise removal is being demanded as preprocessing. In this thesis, for the restoration of image damaged by the noise of random impulse, a switching filter algorithm based on noise estimation was suggested. With the proposed algorithm, noise estimation and error distraction were carried out according to the similarity of the pixel values in the local mask of the image, and a filter was chosen and switched depending on the ratio of noise existing in the local mask. Simulations were conducted to analyze the noise removal performance of the proposed algorithm, and as a result of magnified image and PSNR comparison, it showed superior performance compared to the existing method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.916-918
• /
• 2015

Image processing is being spotlighted as an important sector with increasingly diverse applications as the society advances into a sophisticated digital information age. Especially, the image restoration as the core technology of image processing, many studies are being progressed. In this paper, in order to restore the damaged image in the Salt and Pepper noisy environment, a modified adaptive switching median filter where the size of local mask can be varied according to the noise density was proposed. And using the PSNR as the standard for objective decision making of the improvement effect, it was compared with the existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.434-436
• /
• 2022

For 4th industrial revolution and the development of various communication media, unmanned and automation are rapidly progressing in various fields. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. Accordingly, the importance of preprocessing in a system operating based on an image is increasing, and an algorithm for effectively removing noise from an image is attracting attention. In this paper, we propose a filtering algorithm using noise judgment and a segmentation mask in a complex noise environment. The proposed algorithm calculates the final output by switching the segmentation mask suitable for filtering by performing noise judgment on the pixel values of the input image. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared and evaluated with the existing filter algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.43 no.8 s.350
• /
• pp.91-96
• /
• 2006

High efficiency switching mode circuits such as class I amplifiers have been well known in the MHz frequency range. The class E amplifier is a type of switching mode amplifier offering very high efficiency approaching 100%. In this paper, the class E amplifier has been designed by using the harmonic balance method of circuit simulator. The designed amplifier is realized by using pHEMT and microstrip line, shows 66% power added efficiency (PAE) at 2.4GHz with 17.6dBm output power. With -3dBm input power of wireless LAN, measured output spec01m can meet the required IEEE 802.11g standard spectrum mask. That means the required amplifier back off of 9dB from $P_{ldB}$ to satisfy the required wireless LAN spectrum mask.

• Journal of the Institute of Convergence Signal Processing
• /
• v.21 no.3
• /
• pp.113-120
• /
• 2020

With the recent development of communication equipment, the demand for communication equipment is gradually increasing. Accordingly, various signal processing has been studied. In the case of an image, noise removal is an indispensable step because noise propagation problems may occur if noise is not removed in the pre-processing process. Salt and Pepper noise is a typical impulse noise with two extremes. Various studies have been conducted to remove such noise, and there are CWMF, MF and MMF. However, the existing methods are somewhat insufficient in the high-density noise region. Therefore, in this study, we have proposed an algorithm that filters the size of the mask according to the number of noises inside the 7×7 mask and filters it with a modified switching filter using the histogram distribution of the image. In the case of the proposed algorithm, noise can be effectively removed in a high-density noise region. For objective judgment, PSNR was used to compare and analyze with existing algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.431-433
• /
• 2022

With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. Image denoising is one of the basic processes of image processing, and is used as a preprocessing step in many applications. 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 special noise removal. In this paper, we propose a digital filter using an extended convolutional mask to preserve image detail during the impulse denoising process. The proposed algorithm uses an extended convolution mask as a filtering mask, and obtains the final output by switching the extension level according to the noise level. Simulation was conducted to evaluate the performance of the proposed algorithm, and the performance was analyzed compared to the existing method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.804-806
• /
• 2014

During the transmission process of processing of image, various noises are added causing an error to the image. In order to restore these images, methods such as alpha trimmed average filter, standard median filter and switching median filter were proposed but such previous methods has insufficient noise suppression characteristics. Therefore in this paper, in order to remove the impulse noise added to the image, an adaptive median filter algorithm modified to expand the mask according to the noise density of mask pixels was proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.477-481
• /
• 2009

In this paper the process of transmitting images signal restore to image corrupted by impulse noise proposed switching mean filter. these filter is differential size using the two state noise detection distinguishes noise pixel and noise free pixel. Follow the detected impulse noise density in the image remove the impulse noise using switching mean filter these substituted pixel in order to non-recursive and recursive form from control process of the next pixel comes to be used with neighbor pixel process. Through the simulation, we compared with the existing methods and capabilties.