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Granulation segmentation of the solar photosphere is important step to obtain correct morphometric measures. In this paper, we present a novel method, using morphological technique, for granules segmentation in the solar photosphere. Firstly, a morphological filtering, employing opening-by-reconstruction and closing-by-reconstruction, is used to eliminate image noise. Secondly, Otsu technique is implemented...
We present a non-monotonic gradient descent algorithm with infeasible iterates for the nonnegatively constrained least-squares deblurring of images. The skewness of the intensity values of the deblurred image is used to establish a criterion for when to enforce the nonnegativity constraints. The approach is observed on several test images to either perform comparably to or to outperform a non-monotonic...
Computed Tomography (CT) scanners evolved from simple parallel-beam geometry into more complex fan-beam geometry. The rebinning mechanism to convert fan-beam projections to parallel-beam projections is one of the methods simplifying the reconstruction of the CT image. Various interpolation methods result in different numerical presentations and noisy textures in the reconstructed CT images. This paper...
Image super resolution (SR) reconstruction technique is receiving increasing attention from the image processing community, and it has been widely used in many applications such as remote sensing image, medical image, video surveillance and high definition television. The essential of image SR reconstruction technique is how to produce a clearly high resolution (HR) image from the information of one...
This paper describes a novel method for preprocessing of microscopy images by means of denoising and contrast enhancement in the wavelet domain. A non-linear enhancement function has been designed based on the local dispersion of the wavelet coefficients modelled as a bivariate Cauchy distribution. Within the same statistical framework, a simultaneous noise reduction in the image is performed by means...
With low-dose scanning protocol, CT images are often severely corrupted by quantum noise and artifacts. Artifacts often take prominent directional features and are rather hard to be suppressed without blurring tissue structures. In this paper, we propose to improve low-dose CT (LDCT) images using a two-step scheme called “artifact suppressed dictionary learning algorithm” (ASDL). In the first step,...
This paper deals with the analysis of performance of Canny and Laplacian of Gaussian filter in edge detection of retinal images. Edge detection is one of the methods in image segmentation in Image Processing. Classical methods of edge detection involve convolving the image with an operator (a 2D filter), which is constructed to be geometry of the operator which determines a characteristic direction...
Restoration of the image corrupted by impulse noise is proposed in this paper. Adaptive neuro fuzzy inference system (ANFIS) has been used to detect the impulse noisy pixels to keep preserve the fine details of the image. Feed-forward neural network with resilient backpropagation method is used to estimate the value of the pixel by which the corrupted pixel is replaced by the estimated value. Proposed...
Digital image processing is mainly focused on ever expanding and dynamic area with applications reaching out into our day today life such as medicine, security purpose, space exploration, surveillance, identification & authentication, automatic industry inspection etc. Applications such as these involve different operations like image enhancement, object detection and Noise removing. Implementing...
Acid rain is a major regional scale environmental problem around the globe. To control acid rain pollution and to protect the ecological environment, it is a major need to identify the occurrence of acid rains. This paper presents a methodology for identifying the occurrence of acid rain using pH values calculated from normality by applying k-means clustering and haar wavelet transform on the satellite...
This paper presents an orchid disease detection system using image processing and fuzzy logic. The main objective of this paper is to design a system that is able to detect an orchid disease by processing its leaf image. The system consists of two parts, image processing and fuzzy logic. The leaf image processing uses methods like grayscaling, threshold segmentation and noise removing. The data collected...
This paper discusses a method to extract character strings from scene images. In this method, the Canny edge detector is first applied to a scene image, and the binary edge image is then obtained. Next, small edge elements are separated from large edge elements because edge elements from characters are much smaller than edge elements from non-character objects such as signboards etc. However, many...
Computation of the Euler number of a binary image is often necessary in image matching, image database retrieval, image analysis, pattern recognition, and computer vision. This paper proposes an improvement on the Euler number computing algorithm used in the famous image processing tool MATLAB. By use of the information obtained during processing the previous pixel, the number of times of checking...
Line detection in gray-scale images is a low-level processing which has many applications such as road detection in remote images and vessel detection in medical images. An efficient primitive connection-based algorithm for detecting line segments is proposed. Canny operator is used to detect edges in a digital image and all the edges are tracked to form series of edge point chains by a 4-neighbor-priority...
The additive white Gaussian noise (AWGN) is usually assumed in many image processing algorithms. However, these algorithms cannot effectively deal with the noise from actual cameras which is better modeled as signal dependent noise (SDN). In this paper, we focus on the SDN model and propose an algorithm to accurately estimate its parameters without any assumption of the noise types. The noise parameters...
To solve the problem that the single-peak and sensitivity of conventional image sharpness functions come down which results in slowing auto-focusing speed or even falling to focus because of noise, an anti-noise auto-focusing algorithm is proposed in this paper. The algorithm uses an anti-noise image sharpness function and a searching strategy that combines coarse focusing with fine focusing to improve...
Quartz wafer inevitably produces various physical defects in the production process. This paper focuses on the quartz wafer dirt defects, and proposes a way for image processing on the quartz wafer by using of computer vision library OpenCV. The proposed method is to find contours of the processed images to judge whether there is dirt or not. Experiments show that this method can well detect the dirt...
Localization of a single fluorescent particle with sub-diffraction limit accuracy is a key merit in fluorescence microscopy. Implementation of nonlinear filtering algorithms prior the localization process can improve the localization accuracy of standard existing methods and also enable the localization of overlapping particles, allowing the use of increased fluorophore activation density, and thereby...
Blind source separation (BSS) aims to estimate unknown sources from their mixtures. Methods to address this include the benchmark ICA, SCA, MMCA, and more recently, a dictionary learning based algorithm BMMCA. In this paper, we solve the separation problem by using the recently proposed SimCO optimization framework. Our approach not only allows to unify the two sub-problems emerging in the separation...
The thyroid gland is highly vascular organ, and lies in the anterior part of the neck just below the thyroid cartilage. Ultrasound imaging is most commonly used to detect and classify abnormalities of the thyroid gland. Other modalities (CT/MRI) are also used. There is a challenge to segment ultrasound medical image which is often blurred and consists of noise as other modalities like CT contains...
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