• Journal of Information Processing Systems
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• 제14권2호
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• pp.539-551
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• 2018

Images are unavoidably contaminated with different types of noise during the processes of image acquisition and transmission. The main forms of noise are impulse noise (is also called salt and pepper noise) and Gaussian noise. In this paper, an effective method of removing mixed noise from images is proposed. In general, different types of denoising methods are designed for different types of noise; for example, the median filter displays good performance in removing impulse noise, and the wavelet denoising algorithm displays good performance in removing Gaussian noise. However, images are affected by more than one type of noise in many cases. To reduce both impulse noise and Gaussian noise, this paper proposes a denoising method that combines adaptive median filtering (AMF) based on impulse noise detection with the wavelet threshold denoising method based on a Gaussian mixture model (GMM). The simulation results show that the proposed method achieves much better denoising performance than the median filter or the wavelet denoising method for images contaminated with mixed noise.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권9호
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• pp.429-434
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• 2006

In this paper, detection based - adaptive windowed nonlinear filter(DB-AWNF) is proposed for removing salt-pepper noise in infrared image. This filter is composed of impulse detector and window-size-variable median filters. Impulse detector checks whether current pixel is impulse or not using range function and nonlinear location estimator. If impulse is detected, current pixel is filtered according to four kinds of local masks by use of median filter. If not, current pixel is delivered to output like identity filter. In Qualitative view, the proposed could have removed heavy corrupted noise up to 30% and reserved the details of image. In quantitative view, PSNR was measured. The proposed could have about 12-31[dB] more improved performance than those of median $(3{\times}3)$ filter and 13-29[dB] more improved performance than those of median $(5{\times}5)$ filter.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 춘계학술대회
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• pp.409-411
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• 2016

Salt and pepper 잡음은 카메라 오작동, 저장 매체의 메모리 오류, 전송 채널 에러 등 다양한 원인으로 발생한다. 기존의 salt and pepper 잡음을 제거하기 위한 대표적인 필터에는 SMF(standard median filter), CWMF(center weighted median filter), AMF(adaptive median filter) 등이 대표적이다. 그러나 기존의 필터들은 고밀도 salt and pepper 잡음 환경에서 잡음 제거 특성이 다소 미흡하다. 따라서 본 논문에서는 잡음 판단을 통해 중심화소가 비잡음인 경우, 원 화소 그대로 보존하고 잡음인 경우, 공간 가중치 마스크 및 메디안을 이용한 복합 필터를 제안하였다.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.308-318
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• 2022

Noise is a serious issue. While sending images via electronic communication, Impulse noise, which is created by unsteady voltage, is one of the most common noises in digital communication. During the acquisition process, pictures were collected. It is possible to obtain accurate diagnosis images by removing these noises without affecting the edges and tiny features. The New Average High Noise Density Median Filter. (HNDMF) was proposed in this paper, and it operates in two steps for each pixel. Filter can decide whether the test pixels is degraded by SPN. In the first stage, a detector identifies corrupted pixels, in the second stage, an algorithm replaced by noise free processed pixel, the New average suggested Filter produced for this window. The paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. In this paper the comparison of known image denoising is discussed and a new decision based weighted median filter used to remove impulse noise. Using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structure Similarity Index Method (SSIM) metrics, the paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. A detailed simulation process is performed to ensure the betterment of the presented model on the Mini-MIAS dataset. The obtained experimental values stated that the HNDMF model has reached to a better performance with the maximum picture quality. images affected by various amounts of pretend salt and paper noise, as well as speckle noise, are calculated and provided as experimental results. According to quality metrics, the HNDMF Method produces a superior result than the existing filter method. Accurately detect and replace salt and pepper noise pixel values with mean and median value in images. The proposed method is to improve the median filter with a significant change.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권10호
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• pp.468-476
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• 2002

Digital images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in medical radio-fluoroscopy images is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in diagnosis. We proposed adaptive weighed median(AWM) filters based on local statistics. We showed two ways of realizing the AWM filters. One is a simple type of AWM filter, which is constructed by Homogeneous factor(HF). Homogeneous factor(HF) from the noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the diagnostic systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by Visual C++ language on a IBM-PC Pentium 550 for testing purposes and the effects and results of the filter in the various levels of noise and images were proposed by comparing the values of NMSE(normalized mean square error) with the value of the other existing filtering methods.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 춘계학술대회
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• pp.922-924
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• 2015

현재 영화, TV, 카메라, 광고 등과 같은 대중 매체를 이용한 영상 처리 기술들이 급속도로 발전되고 있다. 그러나 영상은 데이터를 처리 전송 및 저장하는 과정에서 열화가 발생하며, 주요한 원인은 salt and pepper 잡음이 대표적이다. salt and pepper 잡음을 제거하기 위한 대표적인 필터는 CWMF(center weighted median filter), AMF(adaptive median filter) 등이 있으며, 이러한 필터들은 잡음 밀도가 높아짐에 따라 잡음제거 특성이 다소 미흡해지고 시각적인 오류를 나타낸다. 따라서 본 논문은 salt and pepper 잡음을 효과적으로 제거하기 위해, 4개의 영역으로 세분화된 국부마스크를 적용한 메디안 필터를 제안하였으며, 판단 기준으로 PSNR(peak signal to noise ratio)를 사용하였다.

• Communications for Statistical Applications and Methods
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• 제18권6호
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• pp.871-886
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• 2011

This paper proposes a powerful SVM-ASM filter, the adaptive switching median(ASM) filter based on support vector machines(SVMs), to effectively reduce impulse noise in corrupted images while preserving image details and features. The proposed SVM-ASM filter is composed of two stages: SVM impulse detection and ASM filtering. SVM impulse detection determines whether the pixels are corrupted by noise or not according to an optimal discrimination function. ASM filtering implements the image filtering with a variable window size to effectively remove the noisy pixels determined by the SVM impulse detection. Experimental results show that the SVM-ASM filter performs significantly better than many other existing filters for denoising impulse noise even in highly corrupted images with regard to noise suppression and detail preservation. The SVM-ASM filter is also extremely robust with respect to various test images and various percentages of image noise.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.883-885
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• 2013

영상복원은 영상에 첨가되는 여러가지 잡음을 제거하여 잡음이 영상에 미치는 영향을 줄이는 것이다. 영상복원을 위해, 평균 필터, 메디안 필터, 가중치 필터 등 방법들이 제안되었으나 이러한 기존의 방법들은 잡음제거 및 에지 보존 성능이 미흡하다. 따라서 본 논문에서는 효과적으로 잡음을 제거하기 위해 마스크 메디안 값의 여부에 따라 마스크 크기를 확대 시키는 변형된 적응 메디안 필터 알고리즘을 제안하였다. 그리고 시뮬레이션을 통해 기존의 방법들과 비교하였으며 판단의 기준으로 MSE(mean squared error)를 사용하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.798-801
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• 2014

현재, 디지털 시대의 급속 발전과 함께 멀티미디어 서비스에 대한 수요가 증가되고 있다. 그러나 영상 데이터를 처리, 전송, 저장하는 과정에서 여러 외부 원인에 의해 영상의 열화가 발생되며, 영상 열화의 주된 원인은 잡음에 의한 것으로 알려져 있다. 잡음을 제거하는 대표적인 방법은 CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter), AWMF(adaptive weighted median filter) 등이 있으며, 이러한 방법들은 복합잡음 환경에서의 잡음제거 특성이 다소 미흡하다. 따라서 본 논문에서는 복합잡음을 제거하기 위하여 잡음 판단을 거친 후, 마스크의 메디안 값 및 거리에 의해 적응 가중치를 설정하여 처리하는 영상복원 필터 알고리즘을 제안하였다. 그리고 객관적 판단을 위해 기존의 방법들과 비교하였으며, 판단의 기준으로 PSNR(peak signal to noise ratio)을 사용하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.889-892
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• 2000

본 논문에서는 효과적인 De-interlacing을 위한 Edge based Median Filter와 3-Step AMPD(Adaptive Minimum Pixel Difference Filter)를 제안한다. Motion Adaptive De-interlacing 방법에서 중요한 요소인 Motion Hissing에 의한 에러를 방지하기 위해 입력 영상을 4 가지 유형으로 구분하여 각 영상에 따라 다른 임계 값을 적용하여 정확한 화소 값을 보간 하는AMPD(Adaptive Minimum Pixel Difference) Filter를 사용하며 Moving Diagonal Edge의 효과적인 보간을 위해서 방향 필터를 사용하여 Edge Map을 추출한 뒤 Edge에 따라 가변적인 후보 화소를 선택하는 Edge based Median Filter를 사용하여 성능을 향상시켰다. 또한 입력되는 영상을 움직임 영역, 정지 영역, 경계 영역으로 나누어 적응적으로 보간 하여 연산 효율을 높였다. 제안된 방법은 다양한 영상에 대한 모의실험을 통해 기존의 방법에 비해 뛰어난 성능 개선을 보였다.