Abstract: Image Edge Detection is one of the most important
parts of image processing. In this paper, by fuzzy technique, a new
method is used to improve digital image edge detection. In this
method, a 3x3 mask is employed to process each pixel by means of
vicinity. Each pixel is considered a fuzzy input and by examining
fuzzy rules in its vicinity, the edge pixel is specified and by utilizing
calculation algorithms in image processing, edges are displayed more
clearly. This method shows significant improvement compared to
different edge detection methods (e.g. Sobel, Canny).
Abstract: For cognitive radio networks, there is a major
spectrum sensing problem, i.e. dynamic spectrum management. It is
an important issue to sense and identify the spectrum holes in
cognitive radio networks. The first-order derivative scheme is usually
used to detect the edge of the spectrum. In this paper, a novel
spectrum sensing technique for cognitive radio is presented. The
proposed algorithm offers efficient edge detection. Then, simulation
results show the performance of the first-order derivative scheme and
the proposed scheme and depict that the proposed scheme obtains
better performance than does the first-order derivative scheme.