International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
The convolution theorem for the continuous wavelet tranform
Signal Processing
Hallucinating multiple occluded face images of different resolutions
Pattern Recognition Letters
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
Example-based image super-resolution with class-specific predictors
Journal of Visual Communication and Image Representation
New learning based super-resolution: use of DWT and IGMRF prior
IEEE Transactions on Image Processing
New learning based super-resolution: use of DWT and IGMRF prior
IEEE Transactions on Image Processing
Wavelet-based eigentransformation for face super-resolution
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Hallucinating face by eigentransformation
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Extraction of high-resolution frames from video sequences
IEEE Transactions on Image Processing
Quadratic interpolation for image resampling
IEEE Transactions on Image Processing
Joint MAP registration and high-resolution image estimation using a sequence of undersampled images
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Adaptively quadratic (AQua) image interpolation
IEEE Transactions on Image Processing
Locally adaptive wavelet-based image interpolation
IEEE Transactions on Image Processing
Recursive high-resolution reconstruction of blurred multiframe images
IEEE Transactions on Image Processing
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In this paper, we propose a wavelet-based eigentransformation method for human face hallucination. Our algorithm uses the wavelet transform to decompose interpolated low-resolution (LR) images in the wavelet domain to obtain high-frequency information in three different directions, and employs the eigentransformation method to reconstruct the corresponding finer high-frequency content of the high-resolution (HR) images. The low-frequency content of the HR images in the wavelet domain is estimated based on the interpolated images directly. The resulting high-quality HR faces can be synthesized by using the inverse wavelet transform, with all the estimated coefficients. By combining interpolation and eigentransformation, the reconstructed images are less dependent on the training set selected, and can better preserve the low-frequency content. Thus, the reconstructed images look more like the ground-true HR images, as compared to the original eigentransformation method. Experimental results show that our proposed algorithm outperforms the original eigentransformation and other existing methods for face hallucination in terms of both visual quality and objective measurements.