A New Hybrid Filter Approach for Image Processing

Abstract

Today, with the rapidly advancing technology, the importance of image processing techniques is increasing. Image processing is used in many areas from facial recognition to plant disease identification. One of the important image processing stages is the filtering stage used for smoothing images and object detection. Among these filtering techniques, basic filtering techniques such as mean, median and Gaussian are used in image processing. However, these filtering techniques are known to be insufficient to achieve the desired results in some cases. In this study, a new hybrid filtering approach named Mean-Median-Gaussian (MMG) is presented using these three basic filtering techniques. It has been demonstrated that the obtained MMG hybrid algorithm gives more successful results than these three basic filtering techniques in smoothing the images and determining the boundary lines.

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

“…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.…”

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

“…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,…”