Edge-Detection in Noisy Images Using Independent Component Analysis
نویسندگان
چکیده
منابع مشابه
Noisy images edge detection: Ant colony optimization algorithm
The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...
متن کاملnoisy images edge detection: ant colony optimization algorithm
the edges of an image define the image boundary. when the image is noisy, it does not become easy to identify the edges. therefore, a method requests to be developed that can identify edges clearly in a noisy image. many methods have been proposed earlier using filters, transforms and wavelets with ant colony optimization (aco) that detect edges. we here used aco for edge detection of noisy ima...
متن کاملWavelets for Edge Detection in Noisy Images
-In this paper, we present a wavelet based edge detection technique. Edge detection is an important step in pattern recognition, image segmentation, and scene analysis. The conventional approaches to edge detection fail in presence of noise in images and may cause problems in many applications. But noise is very effectively reduced by wavelet filters without any significant loss in the image re...
متن کاملEdge Detection in Noisy Images Using the Support Vector Machines
In this paper, a new method for edge detection in presence of impulsive noise based into the use of Support Vector Machines (SVM) is presented. This method shows how the SVM can detect edge in an efficient way. The noisy images are processed in two ways, first reducing the noise by using the SVM regression and then performing the classification using the SVM classification. The results presente...
متن کاملTarget Detection in Hyperspectral Images Based on Independent Component Analysis
The paper presents an algorithm based on Independent Component Analysis (ICA) for the detection of small targets present in hyperspectral images. ICA is a multivariate data analysis method that attempts to produce statistically independent components. This method is based on fourth order statistics. Small, man-made targets in a natural background can be seen as anomalies in the image scene and ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ISRN Signal Processing
سال: 2011
ISSN: 2090-5041,2090-505X
DOI: 10.5402/2011/672353