Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital image processing
Edge Direction Preserving Image Zooming: A Mathematical and Numerical Analysis
SIAM Journal on Numerical Analysis
Image interpolation using wavelet based hidden Markov trees
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Image resolution enhancement via data-driven parametric models in the wavelet space
Journal on Image and Video Processing
Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal 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
An edge-guided image interpolation algorithm via directional filtering and data fusion
IEEE Transactions on Image Processing
The Undecimated Wavelet Decomposition and its Reconstruction
IEEE Transactions on Image Processing
Enlargement or reduction of digital images with minimum loss of information
IEEE Transactions on Image Processing
Subpixel edge localization and the interpolation of still images
IEEE Transactions on Image Processing
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In this paper, a new wavelet-based image interpolation algorithm is developed for magnifying the image details so that the visibility of tiny features in a digital image is improved. The algorithm takes the LR image as the low-pass filtered subband of an unknown wavelet transformed high resolution image. Then an initial HR image of size twice the LR image is estimated using zero padding of the details. The HR image is transformed via UWT resulting in four subbands, three of which are related with the high frequency components of the image. In the UWT domain, the LL subband is replaced with the initially estimated HR image and applying the inverse UWT, the final HR image is determined. Experiments conducted with both gray level and color images show the superiority of the proposed algorithm over the state-of-the-art interpolation methods.