A New Kind of Hybrid Filter Based on the ICM and the Improved Extremum-and-Median Filter

2008 ◽  
Author(s):  
Zhang Xiang-guang
Keyword(s):  
Median Filter ◽  
Hybrid Filter

scholarly journals Hybrid Filter Based on Fuzzy Techniques for Mixed Noise Reduction in Color Images

2019 ◽  
Vol 10 (1) ◽  
pp. 243 ◽  
Author(s):  
Josep Arnal ◽  
Luis Súcar
Keyword(s):  
Noise Reduction ◽  
Gaussian Noise ◽  
State Of The Art ◽  
Peer Group ◽  
Median Filter ◽  
Block Matching ◽  
Group Method ◽  
Hybrid Filter ◽  
Mixed Noise ◽  
Vector Median

To decrease contamination from a mixed combination of impulse and Gaussian noise on color digital images, a novel hybrid filter is proposed. The new technique is composed of two stages. A filter based on a fuzzy metric is used for the reduction of impulse noise at the first stage. At the second stage, to remove Gaussian noise, a fuzzy peer group method is applied on the image generated from the previous stage. The performance of the introduced algorithm was evaluated on standard test images employing widely used objective quality metrics. The new approach can efficiently reduce both impulse and Gaussian noise, as much as mixed noise. The proposed filtering method was compared to the state-of-the-art methodologies: adaptive nearest neighbor filter, alternating projections filter, color block-matching 3D filter, fuzzy peer group averaging filter, partition-based trimmed vector median filter, trilateral filter, fuzzy wavelet shrinkage denoising filter, graph regularization filter, iterative peer group switching vector filter, peer group method, and the fuzzy vector median method. The experiments demonstrated that the introduced noise reduction technique outperforms those state-of-the-art filters with respect to the metrics peak signal to noise ratio (PSNR), the mean absolute error (MAE), and the normalized color difference (NCD).

scholarly journals A Hybrid Filter for Image Enhancement

2012 ◽  
pp. 45-48
Author(s):  
Vinod Kumar ◽  
Priyanka Priyanka ◽  
Kaushal Kishore
Keyword(s):  
Image Enhancement ◽  
Impulse Noise ◽  
Median Filter ◽  
Wiener Filter ◽  
Image Filtering ◽  
Hybrid Filter ◽  
Object Movement ◽  
Different Types ◽  
The One

Image filtering processes are applied on images to remove the different types of noise that are either present in the image during capturing or introduced into the image during transmission. The salt & pepper (impulse) noise is the one type of noise which is occurred during transmission of the images or due to bit errors or dead pixels in the image contents. The images are blurred due to object movement or camera displacement when we capture the image. This pepper deals with removing the impulse noise and blurredness simultaneously from the images. The hybrid filter is a combination of wiener filter and median filter.

A new kind of hybrid filter based on the intersecting cortical model and the improved Extremum-and-Median filter

2014 ◽  
Vol 19 (2) ◽  
pp. 115-119 ◽  
Author(s):  
Xiangguang Zhang ◽  
Zeyu Zheng ◽  
Ichio Asanuma ◽  
Yongsheng Xu
Keyword(s):  
Median Filter ◽  
Cortical Model ◽  
Hybrid Filter

Adaptive Edge Detection Method for Image Polluted Using Canny Operator and Otsu Threshold Selection

2011 ◽  
Vol 301-303 ◽  
pp. 797-804 ◽  
Author(s):  
Jian Guo Yang ◽  
Bei Zhi Li ◽  
Hua Jiang Chen
Keyword(s):  
Edge Detection ◽  
Gaussian Noise ◽  
Impulse Noise ◽  
Detection Method ◽  
Median Filter ◽  
Threshold Selection ◽  
Hybrid Filter ◽  
Canny Operator ◽  
Mean Filter ◽  
Edge Detection Method

In this paper, an adaptive edge detection method (Canny operator and Otsu threshold selection based adaptive edge detection method - COAED) is proposed. The COAED method combines a new hybrid filter with Canny operator to avoid the conflict of Canny operator between noise removing and edge locating, and uses Otsu threshold selection method to determine Dual-threshold of Canny operator adaptively. The new hybrid filter firstly judges whether the pixel is polluted by impulse noise, and then uses a corresponding filter to process the current pixel. A median filter is used if the pixel is thought to be impulse noise; otherwise an improved mean filter is selected to weaken the Gaussian noise. After the image is smoothed by the hybrid filter, a Canny operator with small Gaussian variance is used to extract edge. Because only part of Gaussian noise remains, Canny operator with small Gaussian variance can suppress the noise and preserve the edge effectively. Using the gauge image polluted by hybrid noise as experiment object, the performance of COAED method is evaluated qualitatively and quantitatively. Experimental results show that the COAED method is superior to Canny operator.

scholarly journals Resonance Image Enhancement using Hybrid Center Weighted Median Filter and Bacteria Foraging Optimization

2020 ◽  
Vol 8 (5) ◽  
pp. 2740-2745
Keyword(s):  
Image Enhancement ◽  
Median Filter ◽  
Hybrid Filter ◽  
Mr Image ◽  
Initial Stage ◽  
Unique Method ◽  
Weighted Median ◽  
Frequency Components ◽  
Weighted Median Filter ◽  
The Brain

Magnetic Resonance Image (MRI) is the best imaging technique employed nowadays for diagnosing brain tumour in the initial stage. This paper recommends an unique method for the brain MR image enhancement, that is centred on the Hybrid Center Weighted Median (HCWM) filter and Bacteria Foraging Optimization (BFO). The MR image for this research is obtained from the online and it is pre-processed to remove all the film artifacts. After that the high frequency components are eliminated from the MR brain image by means of a newly proposed HCWM filter. HCWM Filter is the hybrid filter derived by combining the Center Weighted Median Filter and the Weiner Filter. The swarm-based intelligence algorithm called the bacteria foraging optimization is used to predict the weights of the filter dynamically. The performance of the proposed filtering approach is evaluated with the other available filtering methods.

A Novel Algorithm based on UBTMF for Colour Pictures

2018 ◽  
Vol 8 (4) ◽  
pp. 84
Author(s):  
Himanshu Rehani ◽  
Anuradha Saini
Keyword(s):  
Driving Forces ◽  
Median Filter ◽  
Main Stream ◽  
Points Of Interest ◽  
Novel Algorithm

The issue of picture denoising is one of the most established in the field, is as yet getting extensive focus from the exploration zone due to consistently expanding interest for sensibly valued great media and in additament its part as a pre-preparing venture for picture division, pressure, and so on, because of high spatial being without a vocation of mundane pictures, nearby averaging of the pixels impressively abate the commotion while bulwark the first structure of the picture. To enhance the execution of the essential channels, more compelling sifting calculations including the exchanging vector channels and the amalgamation vector. In spite of the fact that there are different sifting calculations to cull, the more preponderant part of them is not outfit predicated. Multifarious Median Filter (AMF) performs well at low commotion densities. Be that as it may, at high filter densities the window measure must be expanded which may prompt obscuring the picture. In exchanging middle channel the cull depends on Re-characterized limit esteem. The paramount downside of this technique is that characterizing a vigorous cull is onerous. Supplementally these channels won't consider the nearby highlights because of which points of interest and edges may not be recouped severely, concretely when the filter level is high. To vanquish the above downside, Decision Predicated Algorithm (DBA) is proposed. In this, the picture is denoised by utilizing a 3x3 window. On the off chance that the preparing pixel esteem is 0 or 255 it is handled or else it is left unaltered. At high commotion thickness the middle esteem will be 0 or 255 which is boisterous. The goal of disuniting is to expel the driving forces so the commotion free picture is planarity recouped with least flag bending. Filter (Clamor) expulsion can be accomplished by utilizing sundry subsisting direct dissevering procedures which are main stream as a result of their numerical straightforwardness and the presence of the assembling direct framework hypothesis. In spite of the fact that middle channels expel motivation clamor without harming the edges, the prodigious majority of them work consistently over the picture and in this way have a propensity to alter both commotion and clamor free pixels. Preferably, the disuniting ought to be connected just to debased pixels while leaving uncorrupted pixels in place. We propose a novel calculation for clamor diminishment in light of UBTMF for Colour pictures.

An Alternate Algorithm for (3x3) Median Filtering of Digital Images

2012 ◽  
Vol 2 (1) ◽  
pp. 7-9 ◽  
Author(s):  
Satinderjit Singh
Keyword(s):  
Median Filter ◽  
Computational Cost ◽  
Spatial Coherence ◽  
General Purpose ◽  
Median Filtering ◽  
Basic Algorithm ◽  
Temporal Complexity ◽  
Filter Kernel ◽  
One Step ◽  
High Computational Cost

Median filtering is a commonly used technique in image processing. The main problem of the median filter is its high computational cost (for sorting N pixels, the temporal complexity is O(N·log N), even with the most efficient sorting algorithms). When the median filter must be carried out in real time, the software implementation in general-purpose processorsdoes not usually give good results. This Paper presents an efficient algorithm for median filtering with a 3x3 filter kernel with only about 9 comparisons per pixel using spatial coherence between neighboring filter computations. The basic algorithm calculates two medians in one step and reuses sorted slices of three vertical neighboring pixels. An extension of this algorithm for 2D spatial coherence is also examined, which calculates four medians per step.

Enhancing the Performance of One Dimensional Median Filter

2019 ◽  
Vol 118 (7) ◽  
pp. 73-76
Author(s):  
Sharanabasappa ◽  
P Ravibabu
Keyword(s):  
Impulse Noise ◽  
Rank Order ◽  
Median Filter ◽  
Filter Method ◽  
Salt And Pepper Noise ◽  
Edge Preservation ◽  
Word Level ◽  
Look Ahead ◽  
Filter Architecture ◽  
Salt And Pepper

Nowadays, during the process of Image acquisition and transmission, image information data can be corrupted by impulse noise. That noise is classified as salt and pepper noise and random impulse noise depending on the noise values. A median filter is widely used digital nonlinear filter  in edge preservation, removing of impulse noise and smoothing of signals. Median filter is the widely used to remove salt and pepper noise than rank order filter, morphological filter, and unsharp masking filter. The median filter replaces a sample with the middle value among all the samples present inside the sample window. A median filter will be of two types depending on the number of samples processed at the same cycle i.e, bit level architecture and word level architecture.. In this paper, Carry Look-ahead Adder median filter method will be introduced to improve the hardware resources used in median filter architecture for 5 window and 9 window for 8 bit and 16 bit median filter architecture.

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