… distance method of line fitting to adapt it to noisy images, using the maximum likelihood
principle. The method performed quite well in our test cases, and the fitting has greatly improved. …

… In this work, we have proposed a statistical clustering technique for line fitting in noisy
images using the method of the Legendre moments and the maximum entropy principle. The …

… distance method of line fitting to adapt it to noisy images, using the maximum likelihood
principle. The method performed quite well in our test cases, and the fitting has greatly improved. …

… satisfactory, for noisy images difficulties are often encountered. By noisy image data is meant
either of two cases: 1) the amplitude of the noise is large, or 2) the noise amplitude is small …

… Abstract--Finding line segments in an intensity image has … Line features are more robust in
providing greater positional … "line feature extraction" algorithm which extracts line features in a …

… 1 (solid lines). Fig. 2 presents a simple … a noisy image at our disposal, we shall employ
spatial smoothing (as opposed to temporal smoothing, used in [6]) in order to attenuate the noise …

… Since the B-spline model (1) is linear, studying the properties of the basic atoms can tell us
… only approach for fitting a continuous model to a signal. For noisy data, an exact fit may not …

… level function by fitting a lower envelope to the samples of … We could simply fit the noise
function in the learned space to lie … We find that i can be a linear function of the mean noise level …

… by noises. To solve the problems, this paper analyzes the different properties between noise
… regional properties of images points to distinguish noises and object edge points. Based on …

… We present a method to extract the relationship between an image intensity and the noise
… the noise variance and the pixel intensity in the image. The line is a robust least squares fit. …