• The Journal of the Korea Contents Association
• /
• v.9 no.5
• /
• pp.91-98
• /
• 2009

Recent digital camera development tendency shows the higher ISO extension which enables a user to take a picture in deemed lighting condition without using a flash or another equipment. Also noise reduction function has been developed to adjust the higher ISO extension. But using the high ISO causes a lot of noises so that proper noise reduction function should be adjusted. So the manufacturers introduce the advanced noise reduction function with higher ISOs as the digital camera performance development. On the other hands, the defect of noise reduction is not widely open such as remaining noise in high ISOs and decreasing resolution. Therefore, in this research we verify and experiment the decrease of resolution by using noise reduction function on a digital camera. Moreover we analyze the results how much the noise reduction function effects to the image resolution. And we present the results as practical numerical values.

• Nuclear Engineering and Technology
• /
• v.51 no.3
• /
• pp.719-722
• /
• 2019

Gamma-ray images generally suffer from a lot of noise because of low photon detection in the gamma camera system. The purpose of this study is to improve the image quality in gamma-ray images using a gamma camera system with a fast nonlocal means (FNLM) noise reduction algorithm with an acceleration function. The designed FNLM algorithm is based on local region considerations, including the Euclidean distance in the gamma-ray image and use of the encoded information. To evaluate the noise characteristics, the normalized noise power spectrum (NNPS), contrast-to-noise ratio (CNR), and coefficient of variation (COV) were used. According to the NNPS result, the lowest values can be obtained using the FNLM noise reduction algorithm. In addition, when the conventional methods and the FNLM noise reduction algorithm were compared, the average CNR and COV using the proposed algorithm were approximately 2.23 and 7.95 times better than those of the noisy image, respectively. In particular, the image-processing time of the FNLM noise reduction algorithm can achieve the fastest time compared with conventional noise reduction methods. The results of the image qualities related to noise characteristics demonstrated the superiority of the proposed FNLM noise reduction algorithm in a gamma camera system.

• Journal of KSNVE
• /
• v.9 no.5
• /
• pp.949-954
• /
• 1999

Speed-up and mass reduction of railway vehicle usually causes increased of the interior noise. One of the best ways to control the interior noise is to identify the noise level radiated from each of parts in the cabin. In this paper, we describe the method to estimate the interior noise nad evaluate the noise contribution to each of parts. This method is based that the sound pressure can be calculated by using the frequency response function and acceleration. According to analysis of the noise contribution, we validated that the noise radiated from the floor is the higher in the cabin. We also measured the noise distribution for the side and floor by using the microphone array in order to analyze the effect of the noise flowing into the cabin from the outdoors. Finally, we presented the plan of the interior noise reduction based on the noise levels radiated from each of parts.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2010.10a
• /
• pp.340-341
• /
• 2010

Noise reduction is an important factor to design low noise sensor array. In this paper three layers of the de-coupler in the conformal sensor array were used to investigate noise reduction. Conformal sensor array is positioned in the layers and the distance from the layer is 0.25cm~1.5cm. Transfer function in the frequency density function is investigated according to the three different positions. When increasing the embedded distance the flow noise decreased in the region of the kx>10.

• Journal of Environmental Science International
• /
• v.25 no.10
• /
• pp.1407-1415
• /
• 2016

In this study, we investigated the relationship between noise reduction and the community structure of nine groups of typical plant communities as well as the reduction in noise at different frequencies. The semantic differential method was adopted to explore the perception of noise reduction. The results indicated that there was a significantly positive correlation between noise reduction and coverage, a significantly negative correlation between noise reduction and bifurcate height, and a negative correlation between noise reduction and bare rate. However, there was no significant correlation between noise reduction and height, diameter at breast height, or crown width. The reduction of middle-frequency noise was better than that of low- and high-frequency noise. The indicators "quiet" and "calm" showed that plant communities could reduce the noise perceived by humans. However, overly dense woodland caused nervousness, fear, depression, and other negative effects. Relatively open environments and those with large forest gaps obtained the highest evaluation.

• Proceedings of the KSR Conference
• /
• 1999.05a
• /
• pp.218-225
• /
• 1999

Speed-up and mass reduction of EMU(Electrical multiple unit) causes increase of interior noise. One of the best ways to reduce the interior noise is to identify noise sources. In this study, we evaluated interior noise by contribution analysis. This method is to predict the interior noise contribution of carbody by using transfer function between acceleration and sound pressure. The plan of the interior noise reduction based on the test results was also presented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2011.04a
• /
• pp.534-537
• /
• 2011

This Paper present prediction Vehicle Interior Noise using ATF(Acoustic Transfer Function) and engine radiated sound power. This is useful tool to qualifying the effectiveness of Air-borne noise Path. Furthermore This method provide acoustic package performance of the vehicle and able to prepare frequency band to same segment or benchmarking vehicle.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.6
• /
• pp.818-827
• /
• 2008

In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.11a
• /
• pp.73-76
• /
• 2018

A Gaussian noise is caused by surrounding environment or channel interference when transmitting image. The noise reduces not only image quality degradation but also high-level image processing performance. The Non-Local Means (NLM) filter finds similarity in the neighboring sets of pixels to remove noise and assigns weights according to similarity. The weighted average is calculated based on the weight. The NLM filter method shows low noise cancellation performance and high complexity in the process of finding the similarity using weight allocation and neighbor set. In order to solve these problems, we propose an algorithm that shows an excellent noise reduction performance by using Summed Square Image (SSI) to reduce the complexity and applying the weighting function based on a cosine Gaussian kernel function. Experimental results demonstrate the effectiveness of the proposed algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.7
• /
• pp.1127-1140
• /
• 1997

With the study for identifying the transmission characteristics of vibration and noise generated by operating engine system of a vehicle, recently many engineers have studied actively the reduction of vibration and noise inducing uncomfortableness to the passenger. In this study, output noise was analyzed by multi-dimensional spectral analysis and vector synthesis method. The multi-dimensional analysis method is very effective in case of identification of primary source, but this method has little effect on suggestion for interior noised reduction. For compensation of this, vector synthesis method was used to obtain effective method for interior noise reduction, after identifying primary source for output noise. In this paper, partial coherence function of each input was calculated to know which input was most coherent to output noise, then with simulation of changes for input magnitude and phase by vector synthesis diagram, the trends of synthesized output vector was obtained. As a result, the change of synthesized output vector could be estimated.