A New Hybrid Filter Approach for Image Processing

Aksoy, Bekir; Salman, Osamah Khaled Musleh

doi:10.35377/saucis.03.03.785749

Cited by 4 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The simplest option to filtering is to assign a new value to the central pixel as the arithmetic mean of all its neighbors, whose values differ from the central value by no more than a certain threshold. Examples of such filters are rectangular and circular averaging filter [7,9]. More effective noise reduction can be achieved if the effect of the pixels on each other will decrease with distance from the law given by the Gaussian function.…”

Section: Methods Of Filtering Noisy Digital Imagesmentioning

confidence: 99%

Development of Methods for Image Filtering in Noise and their Implementation for a Web Service

Palahin

Palahina

Palahin

2023

Preprint

View full text Add to dashboard Cite

Known image processing software systems use filtering methods such as the Gaussian filter, the median filter, and others, which often do not have satisfactory performance in processing certain types of noise. This leads to a partial loss of the useful signal and a deterioration in image quality. The work is devoted to improving the quality of image filtering in various kinds of noise. A model of additive interaction of signals in additive impulse noise is proposed. A new method of least finite differences (MLFD) and its modification for image filtering has been developed. An interactive web service for the implementation of MLFD was created. Various filtering methods have been proposed to reduce the effect of impulsive noise on images. The proposed data processing is based on a priori information about the type of noise. The web service is a flexible and efficient solution for filtering digital images and is not available in well-known graphics packages. The new web service is a good compromise between the quality of filtering and the simplicity of the solution compared to complex and resource-intensive systems for graphic image processing.

show abstract

Section: Methods Of Filtering Noisy Digital Imagesmentioning

confidence: 99%

Development of Methods for Image Filtering in Noise and their Implementation for a Web Service

Palahin

Palahina

Palahin

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The proposed methodology in this article adopted hybrid filters that combine Mean, Median, and Gaussian filtering. [28] The unwanted noises that are present in the images can be eliminated with median filtering. [29] The median value of the pixels can be calculated by its numerical expression as follows,…”

Section: Hybrid Filter Based Image Pre-processingmentioning

confidence: 99%

Facial Image Segmentation by Integration of Level Set and Neural Network Optimization with Hybrid Filter Pre-processing Model

Rangayya¹,

Patil²,

Patil³

2021

Eng. Sci.

View full text Add to dashboard Cite

Face segmentation is the process of segmenting the visible parts of the face excluding the neck, ears, hair, and beards. In this field, several methods have been developed, but none of them have been effective in providing optimal face segmentation. Hence, we proposed a novel face segmentation method known as level-set-based neural network (NN) algorithm. This method exploits a hybrid filter for the pre-processing of images, which eliminates the unwanted noises and blurring effect from the images. The hybrid filter is the combination of Median, Mean, and Gaussian filters and effectively removes the unwanted noises. Hence the images are segmented by utilizing level-set-based NN algorithm which is commonly based on the population set and effectively reduces the gap between the predicted and expected outcomes. The proposed method is compared with state-of-art methods such as Fully convolution network (FCN), Gabor filter(GF), multi-class semantic face segmentation(MSFS), and genetic algorithms (GA). From the experimental analysis, it is evident that the proposed work achieved better results comparing to other approaches.

show abstract

Optimization of CBCT data with image processing methods and production with fused deposition modeling 3D printing

Sayin,

Aksoy,

Özsoy

2023

Med Biol Eng Comput

View full text Add to dashboard Cite

A New Hybrid Filter Approach for Image Processing

Cited by 4 publications

References 18 publications

Development of Methods for Image Filtering in Noise and their Implementation for a Web Service

Development of Methods for Image Filtering in Noise and their Implementation for a Web Service

Facial Image Segmentation by Integration of Level Set and Neural Network Optimization with Hybrid Filter Pre-processing Model

Optimization of CBCT data with image processing methods and production with fused deposition modeling 3D printing

Contact Info

Product

Resources

About