scholarly journals On the properties of some adaptive morphological filters for salt and pepper noise removal

2021 ◽  
Author(s):  
Marisol Mares-Javier ◽  
Carlos Guillén-Galván ◽  
Rafael Lemuz-López ◽  
Johan Debayle
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Noise Level ◽  
State Of The Art ◽  
Impulsive Noise ◽  
Noise Removal ◽  
Salt And Pepper Noise ◽  
Morphological Filters ◽  
Salt And Pepper

Mathematical Morphology (MM) is a tool that can be applied to many digital image processing tasks that include the reduction of impulsive or salt and pepper noise in grayscale images. The morphological filters used for this task are filters resulting from two basic operators: erosion and dilation. However, when the level of contamination of the image is higher, these filters tend to distort the image. In this work we propose a pair of operators with properties, that better adapt to impulsive noise than other classical morphological filters, it is demonstrated to be increasing idempotent morphological filters. Furthermore, the proposed pair turns out to be a Ʌ-filter and a V-filter which allow to build morphological openings and closings. Finally, they are compared with other filters of the state-of-the-art such as: SMF, PMSF, DBAIN, AMF and NAFSM, and have shown a better performance when the noise level is above 50%.

scholarly journals Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density

2021 ◽  
Vol 11 (2) ◽  
pp. 560
Author(s):  
Manuel González-Hidalgo ◽  
Sebastia Massanet ◽  
Arnau Mir ◽  
Daniel Ruiz-Aguilera
Keyword(s):  
State Of The Art ◽  
Impulsive Noise ◽  
Noise Removal ◽  
Arithmetic Mean ◽  
Salt And Pepper Noise ◽  
Weighted Arithmetic ◽  
Noise Density ◽  
Salt And Pepper ◽  
Robust To Noise ◽  
Restoration Measures

Many computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arithmetic mean aggregation function and the fuzzy mathematical morphology is proposed. The performance of the proposed filter is highly competitive when compared with other state-of-the-art filters regardless of the amount of salt-and-pepper noise present in the image, achieving notable results for any noise density from 5% to 98%. A statistical analysis based on some objective restoration measures supports that this filter surpasses several state-of-the-art filters for most of the noise levels considered in the comparison experiments.

Estimation of qth-Order Fractal Dimensions

Fractals ◽  
1997 ◽  
Vol 05 (supp01) ◽  
pp. 257-269 ◽  
Author(s):  
Stefano Fioravanti ◽  
Daniele D. Giusto
Keyword(s):  
Image Processing ◽  
Fractal Dimension ◽  
Texture Analysis ◽  
Digital Image Processing ◽  
Digital Image ◽  
State Of The Art ◽  
Fractal Dimensions ◽  
Sar Image ◽  
Spectrum Function ◽  
Novel Algorithm

The paper deals with the theory of qth-order fractal dimensions and its application to texture analysis. In particular, the state-of-the-art regarding the fractal dimension estimation for characterizing textures is presented. After, the insufficiency of the single fractal dimension is proven and the qth order fractal dimensions are introduced to overcome such drawback. The multifractality spectrum function D(q) is described, a novel algorithm for estimating such dimensions is then proposed, and its use in digital-image processing is addressed. Results on real SAR image textures are reported and discussed.

scholarly journals High Salt and Pepper Noise Ratio Reduction

2021 ◽  
Vol 10 (9) ◽  
pp. 88-97
Author(s):  
Hatim Zaini ◽  
Ziad Alqadi
Keyword(s):  
Image Processing ◽  
Noise Level ◽  
Digital Images ◽  
Salt And Pepper Noise ◽  
High Noise ◽  
Median Filters ◽  
Negative Effect ◽  
Noise Ratio ◽  
Blurred Images ◽  
Salt And Pepper

Colored digital images are affected by salt and pepper noise, affecting their clarity, contents and properties. The negative effect on the image increases with the increase in the noise level. Filters based on average and median filters are not able to remove SAPN with high noise ratios, and accordingly, blurred images are obtained that cannot be dealt with in various image processing operations. In this paper research a modification will be add to median and average filters making them capable of reducing the noise even it has a high noise ratio, the modified average and median filters will be implanted and some comparisons with other popular filters will be made to show the enhancement of the modified filters.

Decision-Based Marginal Diffusion for Salt-and-Pepper Noise Removal in Color Images

2020 ◽  
pp. 2150153
Author(s):  
Hongyao Deng ◽  
Xiuli Song ◽  
Huilian Fan
Keyword(s):  
Anisotropic Diffusion ◽  
Noise Suppression ◽  
Impulsive Noise ◽  
Geometric Analysis ◽  
Noise Removal ◽  
Diffusion Method ◽  
Salt And Pepper Noise ◽  
The Arts ◽  
Independent Distribution ◽  
Salt And Pepper

Salt-and-pepper noise suppression for vector-valued images usually employs vector median filtering, total variation L1 model, diffusion methods and variants. These approaches, however, often introduce excessive smoothing and can result in extensive visual feature blurring and are suitable only for images with low intensity noise. In this paper, a new method, as an important preprocessing step in cyber-physical systems, is presented to suppress salt-and-pepper noise that can overcomes this limitation. This method first detects the corrupted pixels and then restores them using channel-wise anisotropic diffusion. The means is twofold. On the one hand, the marginal approach is used to perform noise suppression separately in each channel because the contaminative pixel components are of independent distribution. On the other hand, a decision-based anisotropic diffusion method is applied to each channel to restores them. The anisotropic diffusion is an energy-dissipating process with time, and dependent on geometric analysis of shape of the energy surface. Simulation results indicate that the proposed method for impulsive noise removal achieves the state-of-the-arts results.

Digital image processing of airborne geophysical data for uranium‐mineralized breccia pipes exploration in northwestern Arizona

Geophysics ◽  
1990 ◽  
Vol 55 (8) ◽  
pp. 965-976 ◽  
Author(s):  
A. Y. Kwarteng ◽  
P. S. Chavez
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Apparent Resistivity ◽  
Low Frequency ◽  
Noise Removal ◽  
Geophysical Data ◽  
Data Sets ◽  
Overburden Thickness ◽  
Airborne Geophysical Data

Digital image processing and integration of data sets have been used to develop exploration models from airborne electromagnetics (EM), magnetics, and very‐low‐frequency electromagnetics (VLF-EM) data collected over an area in northwestern Arizona. The area has potential for the occurrence of uranium‐mineralized breccia pipes. Apparent resistivity and overburden thickness were derived from the EM measurements using half‐space models. Digital image processing techniques applied to the geophysical data sets included: (1) conversion of the data into gridded‐scale images, (2) spatial filtering for noise removal, (3) integration and analysis of the data sets, and (4) modeling using various parameter combinations. The general relationships between the geophysical variables/parameters and their ability to detect metallic deposits were used as guides in selecting digital number ranges that were used as input into various models. One of the best models incorporated apparent resistivity and total‐field magnetics; the results of this model outlined 13 anomalous combinations in the survey area. Field checking confirmed that two of the anomalies were previously known orebodies, and most of the other anomalies corresponded to suspected pipes that were under evaluation by the group that is exploring the property.

scholarly journals Simulated evaluation of new switching based median filter for suppressing SPN and RVIN

2019 ◽  
Vol 15 (2) ◽  
pp. 688 ◽  
Author(s):  
Vorapoj Patanavijit ◽  
Kornkamol Thakulsukanant
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Impulsive Noise ◽  
Median Filter ◽  
Median Filtering ◽  
Salt And Pepper Noise ◽  
Removal Method ◽  
The Past ◽  
Salt And Pepper ◽  
Objective Indicators

<p>In the past two decades, the SPN (salt and pepper noise) suppressing method is worldwide interested researches on computer vision and image processing hence many SPN suppressing methods have been proposed. In general, the primary goal of SPN removal method is the suppressing of SPN in digital images thereby one of the recent effective and powerful SPN suppressing methods is a new switching-based median filtering (NSMF), which is innovated for suppressing high density SPN. Consequently, this paper thoroughly examines its efficiency and constrain of a new switching-based median filtering when this filter is used for contaminated image, which is synthesized by SPN and RVIN (random-value impulsive noise). In these simulations, six well-known images (Lena, Mobile, Pepper, Pentagon, Girl, Resolution) with two impulsive noise classes (SPN and RVIN) are used for measuring the its efficiency and constrain. An evaluation of the efficiency is conducted with many previous methods in forms of subjective and objective indicators.</p>

scholarly journals Extraction of Pest Insect Characteristics Present in a Mirasol Pepper (Capsicum annuum L.) Crop by Digital Image Processing

2021 ◽  
Vol 11 (23) ◽  
pp. 11166
Author(s):  
Mireya Moreno-Lucio ◽  
Celina Lizeth Castañeda-Miranda ◽  
Gustavo Espinoza-García ◽  
Carlos Alberto Olvera-Olvera ◽  
Luis F. Luque-Vega ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Thrips Tabaci ◽  
Bactericera Cockerelli ◽  
Morphological Filters ◽  
Anthonomus Eugenii ◽  
Pest Insects ◽  
Yellow Traps

One of the main problems in crops is the presence of pests. Traditionally, sticky yellow traps are used to detect pest insects, and they are then analyzed by a specialist to identify the pest insects present in the crop. To facilitate the identification, classification, and counting of these insects, it is possible to use digital image processing (DIP). This study aims to demonstrate that DIP is useful for extracting invariant characteristics of psyllids (Bactericera cockerelli), thrips (Thrips tabaci), whiteflies (Bemisia tabaci), potato flea beetles (Epitrix cucumeris), pepper weevils (Anthonomus eugenii), and aphids (Myzus persicae). The characteristics (e.g., area, eccentricity, and solidity) help classify insects. DIP includes a first stage that consists of improving the image by changing the levels of color intensity, applying morphological filters, and detecting objects of interest, and a second stage that consists of applying a transformation of invariant scales to extract characteristics of insects, independently of size or orientation. The results were compared with the data obtained from an entomologist, reaching up to 90% precision for the classification of these insects.

scholarly journals A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression

2014 ◽  
Vol 2014 ◽  
pp. 1-15
Author(s):  
Hilario Gómez-Moreno ◽  
Pedro Gil-Jiménez ◽  
Sergio Lafuente-Arroyo ◽  
Roberto López-Sastre ◽  
Saturnino Maldonado-Bascón
Keyword(s):  
Support Vector Machines ◽  
Noise Reduction ◽  
Digital Images ◽  
State Of The Art ◽  
Noise Removal ◽  
Support Vector ◽  
Salt And Pepper Noise ◽  
Vector Machines ◽  
Classification And Regression ◽  
Salt And Pepper

We present a new impulse noise removal technique based on Support Vector Machines (SVM). Both classification and regression were used to reduce the “salt and pepper” noise found in digital images. Classification enables identification of noisy pixels, while regression provides a means to determine reconstruction values. The training vectors necessary for the SVM were generated synthetically in order to maintain control over quality and complexity. A modified median filter based on a previous noise detection stage and a regression-based filter are presented and compared to other well-known state-of-the-art noise reduction algorithms. The results show that the filters proposed achieved good results, outperforming other state-of-the-art algorithms for low and medium noise ratios, and were comparable for very highly corrupted images.

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