Alignment tolerance measurement using a DFB laser based on degradation of signal-to-noise ratio owing to speckle noise for short distance multimode optical fibre communication

1996 ◽  
Vol 32 (8) ◽  
pp. 748 ◽  
Author(s):  
S. Koike ◽  
K. Kaizu
Keyword(s):  
Optical Fibre ◽  
Short Distance ◽  
Signal To Noise Ratio ◽  
Speckle Noise ◽  
Signal To Noise ◽  
Dfb Laser ◽  
Optical Fibre Communication ◽  
Noise Ratio ◽  
Multimode Optical Fibre

scholarly journals Novel image enhancement approaches for despeckling in ultrasound images for fibroid detection in human uterus

2021 ◽  
Vol 11 (1) ◽  
pp. 399-410
Author(s):  
Kaitheri Thacharedath Dilna ◽  
Duraisamy Jude Hemanth
Keyword(s):  
Image Processing ◽  
Signal To Noise Ratio ◽  
Ultrasound Image ◽  
Speckle Noise ◽  
Speckle Reduction ◽  
Ultrasound Images ◽  
Signal To Noise ◽  
Statistical Measures ◽  
Noise Ratio ◽  
Scanned Images

Abstract Ultrasonography is an extensively used medical imaging technique for multiple reasons. It works on the basic theory of echoes from the tissues under consideration. However, the occurrence of signal dependent noise such as speckle destroys utility of ultrasound images. Speckle noise is subject to the composition of image tissue and parameters of image. It reduces the effectiveness of many image processing steps and decreases human perception of fine details form ultrasound images. In many medical image processing methods, despeckling is used as the preprocessing step before segmentation and feature extraction. Many speckle reduction filters are proposed but while combining many techniques some speckle diagnostic information should be preserved. Removal of speckle noise from ultrasound image by preserving edges and added features is a great challenging task in ultrasound image restoration. This paper aims at a comprehensive description and comparison of reduction of speckle noise of ultrasound fibroid image. Many filters are applied on ultrasound scanned images and the performance is marked in terms of some statistical measures. Even though several despeckling filters are there for speckle reduction, all are not good for ultrasound scanned images. A comparison of quality measures such as mean square error, peak signal-to-noise ratio, and signal-to-noise ratio is done in ultrasound images in despeckling.

scholarly journals Performance Analysis of Various Filters for De-Speckling of Thyroid Ultrasound Images

2019 ◽  
Vol 9 (2) ◽  
pp. 910-917
Keyword(s):  
Mean Square Error ◽  
Image Quality Assessment ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Mean Square ◽  
Signal To Noise ◽  
Noise Ratio

Thyroid ultrasonography is the most common and extremely useful, safe, and cost effective way to image the thyroid gland and its pathology. However, an inherent characteristic of Ultrasound (US) imaging is the presence of multiplicative speckle noise. Speckle noise reduces the ability of an observer to distinguish fine details, make diagnosis more difficult. It limits the effective implementation of image analysis steps such as edge detection, segmentation and classification. The main objective of this study is to compare the performance of various spatial and frequency domain filters so as to identify efficient and optimum filter for de-speckling Thyroid US images. The performance of these filters is evaluated using the image quality assessment parameters Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Square Error (MSE) and Root Mean Square Error (RMSE) for different speckle variance. Experimental work revealed that kuan filter resulted in higher PSNR, SNR, SSIM and least MSE, RMSE values compared to other filters

scholarly journals Utilizing Statistical Models for Proposing Hybrid Noise Approach of Image Encryption

2018 ◽  
Vol 7 (3.19) ◽  
pp. 20
Author(s):  
Irtefaa A. Neamah ◽  
Hind Rustum Mohammed
Keyword(s):  
Image Encryption ◽  
Statistical Models ◽  
Signal To Noise Ratio ◽  
Hybrid Approach ◽  
Speckle Noise ◽  
Image Noise ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Salt And Pepper ◽  
Image Encryption Algorithm

A proposed strategy for an encryption of image based on image noise by statistical models is represented in this paper. An image encryption algorithm has been designed and simulated for some of the common various types of image noise. The proposed method (Hybrid Noise) consisting of a composition of more than one of probability density functions.Further, the hybrid approach has been compared with some standard noise types such as Gaussian, salt, and pepper, and speckle noise based on some of the performance scales like Peak Signal to Noise Ratio, variance and standard deviation and other comparison tools. The results show that our hybrid method has more security of image with less Peak Signal to Noise Ratio values, which means high noise level.  

A Proposed Approach to De-speckle an Ultrasound Image using Anisotropic Filter by Generating Diffusion Tensor

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Poonam Chauhan ◽  
Vikas Kaushik
Keyword(s):  
Ultrasound Imaging ◽  
Diffusion Tensor ◽  
Signal To Noise Ratio ◽  
Ultrasound Image ◽  
Similarity Index ◽  
Speckle Noise ◽  
The Body ◽  
Invasive Technique ◽  
Signal To Noise ◽  
Noise Ratio

Ultrasound imaging is a technique that is used to diagnose the diseases in medical field using radiology. US (ultrasound) imaging is a non -invasive technique and used for imaging of internal structure of the body without any kind of penetration which helps to identify the diseases that have probability and tissues. Many kinds of noises present in US images but the presence of speckle noise is a big challenge since last few years in biomedical field. Sometimes speckle noise becomes the part of information and vice-versa. So it becomes hard to find the disease for doctors. There are many de-speckled filters available for de-noising. This paper gives a proposed approach to de-speckled the US image using anisotropic diffusion filter by calculating the different numerical values like SSIM (structural similarity index), SNR (signal to noise ratio), MSE (mean square error), PSNR (peak signal to noise ratio), which results in coherence enhancement The proposed technique provides better and improved edge and coherence enhancement in ultrasound image data.

Performance Analysis of Median Filter With Respect to Different Padding Methods in the Context of Removing Salt and Pepper Noise

2019 ◽  
Vol 8 (3) ◽  
pp. 6-9
Author(s):  
T. Sudha ◽  
P. Nagendra Kumar
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Speckle Noise ◽  
Salt And Pepper Noise ◽  
Original Image ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio ◽  
Salt And Pepper

Image Processing is one of the major areas of research. Images are often corrupted with different types of noise such as Gaussian noise, Poisson noise, Salt and Pepper noise, Speckle noise etc.The present work analyses the performance of the median filter with respect to different padding methods in the context of removing salt and pepper noise.Peak Signal-to-Noise ratio and Mean Squared Error have been considered as parameters for performance evaluation. The results obtained show thatthe Peak Signal-to-Noise Ratio and Mean Squared Error obtained between the original image and the filtered image obtained by applying median filter with symmetric padding method on the image corrupted with salt and pepper noise is same as the Peak Signal-to-Noise Ratio and Mean Squared Error obtained between the original image and the filtered image obtained by applying median filter with replicate padding method on the image corrupted with salt and pepper noise respectively.

Noise Reduction, Enhancement and Classification for Sonar Images

2021 ◽  
pp. 4439-4452
Author(s):  
Noor H. Resham ◽  
Heba Kh. Abbas ◽  
Haidar J. Mohamad ◽  
Anwar H. Al-Saleh
Keyword(s):  
Signal To Noise Ratio ◽  
Wiener Filter ◽  
Window Size ◽  
Speckle Noise ◽  
Signal To Noise ◽  
Coherent Noise ◽  
Distance Method ◽  
Sliding Windows ◽  
Noise Ratio ◽  
Four Blocks

    Ultrasound imaging has some problems with image properties output. These affects the specialist decision. Ultrasound noise type is the speckle noise which has a grainy pattern depending on the signal. There are two parts of this study. The first part is the enhancing of images with adaptive Weiner, Lee, Gamma and Frost filters with 3x3, 5x5, and 7x7 sliding windows. The evaluated process was achieved using signal to noise ratio (SNR), peak signal to noise ratio (PSNR), mean square error (MSE), and maximum difference (MD) criteria. The second part consists of simulating noise in a standard image (Lina image) by adding different percentage of speckle noise from 0.01 to 0.06. The supervised classification based minimum distance method is used to evaluate the results depending on selecting four blocks located at different places on the image. Speckle noise was added with different percentage from 0.01 to 0.06 to calculate the coherent noise within the image. The coherent noise was concluded from the slope of the standard deviation with the mean for each noise. The results showed that the additive noise increased with the slide window size, while multiplicative noise did not change with the sliding window nor with increasing noise ratio. Wiener filter has the best results in enhancing the noise.

COMPARISON OF DENOISING FILTERS ON COLOUR TEM IMAGE FOR DIFFERENT NOISE

2013 ◽  
pp. 218-225
Author(s):  
GARIMA GOYAL ◽  
MANISH SINGHAL ◽  
AJAY KUMAR BANSAL
Keyword(s):  
Gaussian Noise ◽  
Signal To Noise Ratio ◽  
Speckle Noise ◽  
Morphological Characterization ◽  
Signal To Noise ◽  
Transmission Electron ◽  
Microscopy Image ◽  
Multiplicative Type ◽  
Noise Ratio ◽  
Performance Results

TEM (Transmission Electron Microscopy) is an important morphological characterization tool for Nanomaterials. Quite often a microscopy image gets corrupted by noise, which may arise in the process of acquiring the image, or during its transmission, or even during reproduction of the image. Removal of noise from an image is one of the most important tasks in image processing. Denoising techniques aim at reducing the statistical perturbations and recovering as well as possible the true underlying signal. Depending on the nature of the noise, such as additive or multiplicative type of noise, there are several approaches towards removing noise from an image. Image De-noising improves the quality of images acquired by optical, electro-optical or electronic microscopy. This paper compares five filters on the measures of mean of image, signal to noise ratio, peak signal to noise ratio & mean square error. In this paper four types of noise (Gaussian noise, Salt & Pepper noise, Speckle noise and Poisson noise) is used and image de-noising performed for different noise by various filters (WFDWT, BF, HMDF, FDE, DVROFT). Further results have been compared for all noises. It is observed that for Gaussian Noise WFDWT & for other noises HMDF has shown the better performance results.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

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