Enlargement for Images with Gaussian Noise by Embedded Filtering in the LP Algorithm
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Warped distance for space-variant linear image interpolation
IEEE Transactions on Image Processing
Regularity-preserving image interpolation
IEEE Transactions on Image Processing
Image enhancement by nonlinear extrapolation in frequency space
IEEE Transactions on Image Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Locally adaptive wavelet-based image interpolation
IEEE Transactions on Image Processing
On the role of exponential splines in image interpolation
IEEE Transactions on Image Processing
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In this paper, we propose an image enlargement method by using morphological operators. Our enlargement method is based on the nonlinear frequency extrapolation method (Greenspan et al., 2000) by using a Laplacian pyramid image representation. In this method, the sampling process of input images is modeled as the Laplacian pyramid. A high resolution image is obtained with the finer scale Laplacian that is extrapolated by a nonlinear operation from a low resolution Laplacian. In this paper, we propose a novel nonlinear operation for extrapolation of the finer scale Laplacian. Our nonlinear operation is realized by morphological operators and is capable of generating the finer scale Laplacian, the amplitude of which is proportional to contrasts of edges that appear in the low resolution image. In experiments, the enlargement results given by the proposed method are demonstrated. Compared with the Greenspan's method, the proposed method can recover sharp intensity transients of image edges with small artifacts.