• Journal of the Institute of Convergence Signal Processing
• /
• v.17 no.2
• /
• pp.71-76
• /
• 2016

Digital image processing is being utilized in various fields including medical industry, satellite photos, and factory automation image recognition. However, this kind of image data produces heat by an external cause in the course of being processed, transmitted, and stored. Most typical noises added in the images are AWGN and salt and pepper. MF, CWMF, and AWMF are methods used to restore images damaged by AWGN and the existing methods are likely to damage detailed information such as an edge. Therefore, this paper suggests an algorithm applying weight of average filter, average filter depending on pixel, and spatial weight filter based on edge size of local mask in an AWGN environment, in a different way. Also, this paper compares functions of existing methods by using PSNR to prove excellence of the suggested algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.7
• /
• pp.910-916
• /
• 2021

In modern society, various digital communication equipment is being used due to the influence of the 4th industrial revolution. Accordingly, interest in removing noise generated in a data transmission process is increasing, and research is being conducted to efficiently reconstruct an image. In this paper, we propose a filtering algorithm to remove the AWGN generated in the digital image transmission process. The proposed algorithm classifies pixels with high similarity by selecting regions with similar patterns around the input pixels according to block matching to remove the AWGN that appears strongly in the image. The selected pixel determines the estimated value by applying the weight obtained by the local steering kernel, and obtains the final output by adding or subtracting the input pixel value according to the standard deviation of the center mask. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and comparative analysis was performed using enlarged images and PSNR.

• Human Ecology Research
• /
• v.52 no.1
• /
• pp.33-42
• /
• 2014

The purpose of this study is to analyze the internal meanings of dolls and dolls' images expressed in modern fashion show. Dolls are used as sacred object, decoration object, playing object, personified object or cherished object. The expression types of doll image in modern fashion are as following; substitutes of multi-ego, object of sexual desire, objectified creature, and medium of transcending fantasy. First, dolls image as substitutes of multi-ego had been expressed in magical expression, disgusting mask, transparent mannequin, expressionless, horror, conflict, loss of identity, exaggeration or escapism. Second, as object of sexual desire, dolls image are expressed as naked baby, ambiguous expression, naked body, voluminous body, emphasized specific bodypart, heavy makeup or wax doll of sexy actresses. Third, as objectified creature, dolls are human body in passive form. Human bodies are disassembled and reassembled as dolls. Such dolls reflect serious reality. They wrap up human like product and objectify it. Fourth, dolls image expressed as medium of transcending fantasy recollects youth age or expresses imagination on ambiguous virtual reality. Like this, dolls have value as creatures in various fields of modern fashion. Dolls contribute a lot in creating important inspiration. Dolls also expose internal mentality and represent ego. Externally, dolls express human shape becoming more and more materialized and objectified by advancing scientific technology in digital capitalistic society.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.12
• /
• pp.2701-2706
• /
• 2009

There are Impulse noise and AWGN in a general image processing. Various methods have been proposed to remove these noises. Well-known filters are Mean, Min-max and Median filter and these show different characteristics depending on the noises. When Impulse noise and AWGN are in superposition environment, single filter doesn't remove noises well. Therefore in this paper, we suggested a switching filter using a probability of noise to restore images in this environment. And we compared a filter with conventional method through simulations.

• Journal of Digital Contents Society
• /
• v.18 no.1
• /
• pp.175-182
• /
• 2017

Noises are usually generated by various external causes and low quality devices in image data acquisition and recording as well as by channel interference in image transmission. Since these noise signals result in the loss of information, subsequent image processing is subject to the corruption of the original image. In general, image processing is performed in the mixed noise environment where common types of noise, known to be Gaussian and impulse, are present. This study proposes an iterative weighted mean filter for reducing mixed type of noise. Impulse noise pixels are first turned off in the input image, then $3{\times}3$ sliding window regions are processed by replacing center pixel with the result of weighted mean mask operation. This filtering processes are iterated until all the impulse noise pixels are replaced. Applied to images corrupted by Gaussian noise with ${\sigma}=10$ and different levels of impulse noise, the proposed filtering method improved the PSNR by up to 12.98 dB, 1.97 dB, 1.97 dB respectively, compared to SAWF, AWMF, MMF when impulse noise desities are less than 60%.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.7
• /
• pp.1687-1693
• /
• 2015

Recently, demand for digital image processing devices increases rapidly, more clear images have been required. But, in the process of digital image acquisition, processing and transmission, image degradation occurs due to various external reasons and researches about noise reduction are on the rise. Therefore, this study suggested the algorithm to process AWGN(additive white Gaussian noise) by separately processing as three levels according to the pixel distribution in the mask in order to remove AWGN(additive white Gaussian noise) which is added in the image. Regarding the processed results by applying Barbara images which were damaged by AWGN(σ = 15), suggested algorithm showed the improvement by 2.87[dB], 2.95[dB], 2.88[dB], 1.52[dB], 1.49[dB], 1.58[dB] and 1.25[dB] respectively compared with the existing MF(5 × 5), A-TMF(5 × 5), AWMF(5 × 5), MF(3 × 3), A-TMF(3 × 3), AWMF(3 × 3), GF(5 × 5).

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.4
• /
• pp.840-846
• /
• 2016

Recently, with the rapid demand expansion on the devices of digital image processing, the excellent quality of the images is required. However, the degradation of the images occurs in the processes of data acquisition, processing, and transmission by various external causes and the noise has been well known as the major cause of image degradation. There are a variety of noises to be added on the images, with typical example of AWGN. Hence, in this article, we suggested average filter algorithm processed by the threshold values using them applying standard deviation of local mask under the AWGN environment in this study. As the result of the simulation, The proposed algorithm shows a high PSNR of 24.56[dB] for Barbara images that had been damaged of AWGN(${\sigma}=15$), compared to the existing MF, CWMF and AWMF there were improvements by 3.34[dB], 2.57[dB], and 3.32[dB], respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.404-406
• /
• 2021

In modern society, artificial intelligence and automation are being applied in various fields due to the development of the 4th industrial revolution and IoT technology. In particular, systems with a high proportion of image processing, such as automated processes, intelligent CCTV, medical industry, robots, and drones, are susceptible to external factors noise. In this paper, we propose a digital filter based on noise estimation and weights to reconstruct an image in a complex noise environment. The proposed algorithm classifies the types of noise using noise judgment, and determines the noise level of the filtering mask to switch the filtering process to obtain the final output. In order to verify the performance of the proposed algorithm, simulation was conducted, compared with the existing filter algorithm, and the results were analyzed.

• 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.

• Smart Structures and Systems
• /
• v.17 no.1
• /
• pp.91-105
• /
• 2016

One of the most commonly used techniques to strengthen steel reinforced concrete structures is the application of externally bonded patches in the form of carbon fiber reinforced polymers (CFRP) or recently, textile reinforced cements (TRC). These external patches undertake the tensile stress of bending constraining concrete cracking. Development of full-field inspection methodologies for fracture monitoring are important since the reinforcing layers are not transparent, hindering visual observation of the material condition underneath. In the present study acoustic emission (AE) and digital image correlation (DIC) are applied during four-point bending tests of large beams to follow the damage accumulation. AE helps to determine the onset of fracture as well as the different damage mechanisms through the registered shifts in AE rate, location of active sources and change in waveform parameters. The effect of wave propagation distance, which in large components and in-situ can well mask the original information as emitted by the fracture incidents is also discussed. Simultaneously, crucial information is supplied by DIC concerning the moments of stress release of the patches due to debonding, benchmarking the trends monitored by AE. From the point of view of mechanics, conclusions on the reinforcing contribution of the different repair methodologies are also drawn.