Intuitionistic Fuzzy Filters for Noise Removal in Images

Author(s):  
C. Radhika ◽  
R. Parvathi ◽  
N. Karthikeyani Visalakshi

Image processing is any form of information processing in which both input and output are images. Most of the image processing involves in treating the image as two dimensional representations and applying standard techniques to it. Images contain lot of uncertainties and are fuzzy/vague in nature. Various fuzzy filtering techniques are defined for noise removal in image processing and these existing filters helps to enhance the image using only the membership values. Further, by incorporating intuitionistic fuzzy filters, vagueness and ambiguity are managed by taking the non-membership values also into consideration. In this paper, light is thrown on some important types of noise and a comparative analysis is done. This paper also presents the results of applying different noise types to an image and investigates the results of various intuitionistic fuzzy filtering techniques. A comparison is made on the results of all the techniques.

Biometrics ◽  
2017 ◽  
pp. 1643-1655
Author(s):  
C. Radhika ◽  
R. Parvathi ◽  
N. Karthikeyani Visalakshi

Image processing is any form of information processing in which both input and output are images. Most of the image processing involves in treating the image as two dimensional representations and applying standard techniques to it. Images contain lot of uncertainties and are fuzzy/vague in nature. Various fuzzy filtering techniques are defined for noise removal in image processing and these existing filters helps to enhance the image using only the membership values. Further, by incorporating intuitionistic fuzzy filters, vagueness and ambiguity are managed by taking the non-membership values also into consideration. In this paper, light is thrown on some important types of noise and a comparative analysis is done. This paper also presents the results of applying different noise types to an image and investigates the results of various intuitionistic fuzzy filtering techniques. A comparison is made on the results of all the techniques.


2018 ◽  
Vol 7 (2.21) ◽  
pp. 351
Author(s):  
T Hemapriya ◽  
K S. Archana ◽  
T Anupriya

Coin is very important role in human’s day life. For daily routine like shop, super market, banks etc the coins to be used. The coin is important part of economies and currency and it is used to pay for goods and also for our needs. Here the Indian coin has many number of count five rupee, ten rupee, two rupee, from this any one of the coin we are going to extract the texture feature for our Indian coin, first step is to preprocess the image is that method to enhance the image and remove the noise from enhanced image. For extracting clear information the image has to be preprocessed through some of the filtering techniques such as image size has to be resized, changing the contrast of the image, changing RGB to grayscale conversion for further operation such as segmentation and classification. At last the values to be compared by using PSNR, SNR, MSE of Filter noise removal with respective coin images.  


2013 ◽  
Vol 718-720 ◽  
pp. 2159-2162
Author(s):  
Hua Jun Dong ◽  
Xue Mei Jiang ◽  
Chen Xu Niu

The existence of noises have great interference on image processing, so the elimination of image noise is of great importance. In this paper, based on the digital image processing, the methods of average filter, wiener filter, median filter, two-dimensional wavelet filter, maximum and minimum filter are used to eliminate the salt & pepper noise of image. Then we analysis and compare the results of the five methods to find the best way to eliminate the image noise.


2018 ◽  
Vol 7 (2.2) ◽  
pp. 70
Author(s):  
Darius Shyafary ◽  
Rony H ◽  
Rheo Malani ◽  
Anggri Sartika W

A mosaic is a combination of two or more images with various combining techniques. One of the computer graphics applications is the image mosaic used for various purposes such as texture maps and better image backgrounds. One of the important things in making image mosaic is how to create small pieces of the image in such a way that it produces a good image mosaic. A number of methods have been proposed to build an image mosaic system that produces good mosaic results, but it usually requires complicated calculations. Fuzzy image processing is a form of information processing that input and output both images. This is a collection of fuzzy approaches that understand, represent and process their images, segments, and features as a fuzzy set. In this study, fuzzy image processing concept is used to create image mosaic by random seed generation using Fuzzy Membership Function (MF).  


2000 ◽  
Vol 179 ◽  
pp. 229-232
Author(s):  
Anita Joshi ◽  
Wahab Uddin

AbstractIn this paper we present complete two-dimensional measurements of the observed brightness of the 9th November 1990Hαflare, using a PDS microdensitometer scanner and image processing software MIDAS. The resulting isophotal contour maps, were used to describe morphological-cum-temporal behaviour of the flare and also the kernels of the flare. Correlation of theHαflare with SXR and MW radiations were also studied.


Author(s):  
U. Aebi ◽  
L.E. Buhle ◽  
W.E. Fowler

Many important supramolecular structures such as filaments, microtubules, virus capsids and certain membrane proteins and bacterial cell walls exist as ordered polymers or two-dimensional crystalline arrays in vivo. In several instances it has been possible to induce soluble proteins to form ordered polymers or two-dimensional crystalline arrays in vitro. In both cases a combination of electron microscopy of negatively stained specimens with analog or digital image processing techniques has proven extremely useful for elucidating the molecular and supramolecular organization of the constituent proteins. However from the reconstructed stain exclusion patterns it is often difficult to identify distinct stain excluding regions with specific protein subunits. To this end it has been demonstrated that in some cases this ambiguity can be resolved by a combination of stoichiometric labeling of the ordered structures with subunit-specific antibody fragments (e.g. Fab) and image processing of the electron micrographs recorded from labeled and unlabeled structures.


1998 ◽  
Vol 10 (1-3) ◽  
pp. 100-108 ◽  
Author(s):  
Alicia Colson ◽  
Ross Parry

This article argues that the analysis of a threedimensional image demanded a three-dimensional approach. The authors realise that discussions of images and image processing inveterately conceptualise representation as being flat, static, and finite. The authors recognise the need for a fresh acuteness to three-dimensionality as a meaningful – although problematic – element of visual sources. Two dramatically different examples are used to expose the shortcomings of an ingrained two-dimensional approach and to facilitate a demonstration of how modern (digital) techniques could sanction new historical/anthropological perspectives on subjects that have become all too familiar. Each example could not be more different in their temporal and geographical location, their cultural resonance, and their historiography. However, in both these visual spectacles meaning is polysemic. It is dependent upon the viewer's spatial relationship to the artifice as well as the spirito-intellectual viewer within the community. The authors postulate that the multi- faceted and multi-layered arrangement of meaning in a complex image could be assessed by working beyond the limitations of the two-dimensional methodological paradigm and by using methods and media that accommodated this type of interconnectivity and representation.


2012 ◽  
Vol 9 (1) ◽  
pp. 47-52
Author(s):  
R.Kh. Bolotnova ◽  
V.A. Buzina

The two-dimensional and two-phase model of the gas-liquid mixture is constructed. The validity of numerical model realization is justified by using a comparative analysis of test problems solution with one-dimensional calculations. The regularities of gas-saturated liquid outflow from axisymmetric vessels for different geometries are established.


Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1079
Author(s):  
Vladimir Kazakov ◽  
Mauro A. Enciso ◽  
Francisco Mendoza

Based on the application of the conditional mean rule, a sampling-recovery algorithm is studied for a Gaussian two-dimensional process. The components of such a process are the input and output processes of an arbitrary linear system, which are characterized by their statistical relationships. Realizations are sampled in both processes, and the number and location of samples in the general case are arbitrary for each component. As a result, general expressions are found that determine the optimal structure of the recovery devices, as well as evaluate the quality of recovery of each component of the two-dimensional process. The main feature of the obtained algorithm is that the realizations of both components or one of them is recovered based on two sets of samples related to the input and output processes. This means that the recovery involves not only its own samples of the restored realization, but also the samples of the realization of another component, statistically related to the first one. This type of general algorithm is characterized by a significantly improved recovery quality, as evidenced by the results of six non-trivial examples with different versions of the algorithms. The research method used and the proposed general algorithm for the reconstruction of multidimensional Gaussian processes have not been discussed in the literature.


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