• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.922-924
• /
• 2015

Recently, the image processing technologies using the public media such as the film, TV, camera and advertisement have been rapidly developed. However, the deterioration occurs with the image in the process of data processing, transmission and storage, and the typical cause of such deterioration is the salt and pepper noise. Typical filters to remove the salt and pepper noise include CWMF(center weighted median filter) and AMF(adaptive median filter) but such filters bring more or less insufficient characteristics of noise removal and visual error as the noise density gets higher. Thus, this paper proposed the median filter which applied the local mask segmented to 4 areas in order to remove the salt and pepper noise effectively and used PSNR(peak signal to noise ratio) as a criterion of judgment.

• Journal of Information Processing Systems
• /
• v.14 no.2
• /
• pp.539-551
• /
• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.409-411
• /
• 2016

Salt and pepper noise is caused by various causes such as camera malfunction, storage media memory error, and transmission channel error. Representative filters to remove salt and pepper noise include SMF(standard median filter), CWMF(center weighted median filter), and AMF(adaptive median filter). However previous filters have inadequate noise removal characteristics in high density salt-and-pepper noise environment. Therefore the study suggested a composite filter which, through noise evaluation, preserves original pixels when the central pixel is non-noise, and uses spatial weighted value mask and median when there is noise.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.308-318
• /
• 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.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.6
• /
• pp.65-71
• /
• 2017

Digital images and videos are subject to various types of noise during storage and transmission. Among these noises, Salt & Pepper noise degrades the compression efficiency of the original data and causing deterioration of performance in edge detection or segmentation used in an image processing method. In order to mitigate this noise, there are many filters such as Median Filter, Weighted Median Filter, Center Weighted Median Filter, Switching Weighted Median Filter and Adaptive Median Filter. However these methods are inferior in performance at high noise density. In this paper we propose a new type of filter for noise mitigation in wireless communication environment where Salt & Pepper noise occurs. The proposed filter detects the location of the damaged pixel by Salt & Pepper noise detection and mitigates the noise by using adjacent pixel values which are not damaged in a certain area. Among the proposed filters, the performance of the filter using the $3{\times}3$ error mask is compared with that of the conventional methods and it is confirmed that when density of noise in the image is 95%, their performances are improved as 13.24 dB compared to MF and 13.09 dB compared to AMF.

• The Journal of the Korea Contents Association
• /
• v.6 no.4
• /
• pp.11-18
• /
• 2006

A new algorithm for removing salt and pepper impulse noise in image using impulse noise detector and total variation optimization is presented. The proposed two types of noise detectors which are based on the adaptive median filter, can detect impulse noise with high accuracy while reducing the probability of detecting image details as impulses. And the detectors maintain its performance independent of noise density. For removing impulses, total variation optimization is applied only to those detected noise candidate to reduces unnecessary computation. The proposed approach successfully remove impulse noise while preserving image details.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.903-905
• /
• 2015

The need for digital devices is increasing in the digital age. In general, noise in images occurs during the process of compression, recognition and processing due to many reasons. Some of the filters used to remove salt and pepper noise include SMF, CWMF and AMF. In areas where the noise density is high, the removal of noise is undermined. This paper suggests an adjusted median filter algorithm that preserves the non-noise pixels while transforming the noise pixels to more effectively remove salt and pepper noise.