• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.371-380
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• 2011

The noise caused by a variety of reasons worsens the quality of input image when we use the images reproducing device. The basic difficulty to solve this problem is that the noise and the signal are difficult to be distinguished. Contrast enhancement such as unsharp masking is one of the most important procedures to improve the quality of input images. The conventional unsharp masking enhances the images by adding their amplified high frequency components. The noise component of the input images, however, also tends to be amplified due to the nature of the unsharp masking. This paper considers the block approach for detecting niose and image feature of the input image so that the unsharp masking could be adaptively applied accordingly. Simulation results show that it is made possible to enhance contrast of the image without boosting up the noisy components by applying the proposed algorithm.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.599-602
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• 1998

In this paper, a speech enhancement method based on phonemic properties and masking effect is propsoed. It is a modified type of spectral subtraction wherein the spectral sharpening process is exploited in unvoiced state considering the phonemic properties. The masking threshold is used to remove the residual noise. The proposed spectral subtraction shows similar performance as that of the classical spectral subtraction method in view of the SNR. But by the prposed scheme, the unvoiced sound region is shown to exhibit relatively less signal distortion in the enhanced speech.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.505-510
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• 2014

Normalized Difference Vegetation Index (NDVI) is a major indicator for monitoring climate change and detecting vegetation coverage. In order to retrieve NDVI, it is preprocessed using cloud masking and atmospheric correction. However, the preprocessed NDVI still has abnormally low values known as noise which appears in the long-term time series due to rainfall, snow and incomplete cloud masking. An existing method of using polynomial regression has some problems such as overestimation and noise detectability. Thereby, this study suggests a simple method using amoving average approach for correcting NDVI noises using SPOT/VEGETATION S10 Product. The results of the moving average method were compared with those of the polynomial regression. The results showed that the moving average method is better than the former approach in correcting NDVI noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.929-934
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• 2007

Various methods to improve the planetary gear noise in the vehicle were introduced. And planetary gear systems were analyzed Therefore a common thing among the different planetary gear systems which generate the gear noise in the vehicle was founded. Most importantly, a frequency versus vibration level map was introduced and a predictive method, which is considering the masking effect, to design the planetary gear sets in the concept design stage was described.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.215-218
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• 2003

In this paper we apply PMC (parallel model combination) to speech recognition system online. As a representative of model based noise compensation techniques, PMC compensates environmental mismatch by combining pretrained clean speech models and real-time estimated noise information. This is very effective approach for compensating extreme environmental mismatch but is inadequate to use in on-line system for heavy computational cost. To reduce the computational cost and to apply PMC online, we use a noise masking effect - the energy in a frequency band is dominated either by clean speech energy or by noise energy - in the process of model compensation. Experiments on artificially produced noisy speech data confirm that the proposed technique is fast and effective for the on-line model compensation.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1984.10a
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• pp.88-91
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• 1984

In component coding, it si well known that a Luminance edge provides better masking of the noise added to chrominance signals. So we propose an adapive DPCM coding system which provides good performance in chromainance signals by using the effect of this masking.

• Journal of IKEEE
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• v.13 no.2
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• pp.224-231
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• 2009

Unsharp masking is a popular image enhancement technique used to sharpen an image appearance in gray images. However, the conventional unsharp making techniques amplify the noise and easily cause overshoot artifacts. Moreover, the unsharp masking tends to introduce color distortion when it is applied to the each color component independently. To solve these problems, we propose a novel unsharp masking technique based on human visual system and vector projection. The proposed algorithm consists of two steps. First, the proposed algorithm controls the level of sharpening by exploiting the characteristics of the human visual system and contrast region. Then the vector projection is applied to remove the color distortion. Experiment results show that our proposed algorithm successfully produces sharpened images that are free of noise and color distortion commonly found in the conventional unsharp masking algorithms.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.43-46
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• 1991

In this study, peripheral auditory system has been modeled as a filter bank of overlaping bandpass filters, and auditory filter shape has been estimated by notch noise masking. The filter was centered at 1kHz, and noise level was set to 40dB SPL. Masker noise was generated by summing sinusoidal functions with random phase for very steep skirts. To estimate threshold we used two alternative forced choice with 500 msec of duration. We measured threshold with notch width at 0.05,0.1,0.2,0.3,0.4 and 0.5. The filter was asymmetric with steeper upper branch and its ERB was 168 - 192 Hz.

• Speech Sciences
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• v.4 no.2
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• pp.5-15
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• 1998

This paper proposes a speech state-dependent spectral subtraction method to regulate the blind spectral subtraction for improved enhancement. In the proposed method, a modified subtraction rule is applied over the speech selectively contingent to the speech state being voiced or unvoiced, in an effort to incorporate the acoustic characteristics of phonemes. In particular, the objective of the proposed method is to remedy the subtraction induced signal distortion attained by two state-dependent procedures, spectrum sharpening and minimum spectral bound. In order to remove the residual noise, the proposed method employs a procedure utilizing the masking effect. Proposed spectral subtraction including state-dependent subtraction and residual noise reduction using the masking threshold shows effectiveness in compensation of spectral distortion in the unvoiced region and residual noise reduction.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.991-996
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• 1994

Surrounding noise often affects the performance of speech recognition system when it is used in office or home. Especially situation is more serious when colored and nonstational noise such as an sound from television or other audio equipment is introduced. The authors proposed a voice control system for television set using an adaptive noise canceler, and it works well even is sound of television set has comparable level of speech. In this paper, a new front-end of speech recognition is introduced for the voice control system. This font-end utilizes a simplified masking model to reduce the effect of residual noise. According to experimental results, 90% correct recognition is achieved even if the level of television sound is almost 15dB higher than one of speech.