Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Breakdown of equivalence between the minimal l1-norm solution and the sparsest solution
Signal Processing - Sparse approximations in signal and image processing
Face Hallucination: Theory and Practice
International Journal of Computer Vision
Journal of Cognitive Neuroscience
Determining the regularization parameters for super-resolution problems
Signal Processing
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Image and Vision Computing
Hallucinating face by position-patch
Pattern Recognition
Image super-resolution via sparse representation
IEEE Transactions on Image Processing
Face Hallucination under an Image Decomposition Perspective
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Hallucinating face by eigentransformation
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Image Processing
The curvelet transform for image denoising
IEEE Transactions on Image Processing
Eigenface-domain super-resolution for face recognition
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image decomposition via the combination of sparse representations and a variational approach
IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
Morphological Component Analysis: An Adaptive Thresholding Strategy
IEEE Transactions on Image Processing
From Local Pixel Structure to Global Image Super-Resolution: A New Face Hallucination Framework
IEEE Transactions on Image Processing
| Hi-index | 0.08 |
In this paper, we formulate the face hallucination as an image decomposition problem, and propose a Morphological Component Analysis (MCA) based method for hallucinating a single face image. A novel three-step framework is presented for the proposed method. Firstly, a low-resolution input image is up-sampled via an interpolation. Then, the interpolated image is decomposed into a global high-resolution image and an unsharp mask by using MCA. Finally, a residue compensation is performed on the global face to enhance its visual quality. In our proposal, the MCA plays a vital role as MCA can properly decompose a signal into several semantic sub-signals in accordance with specific dictionaries. By virtue of the multi-channel decomposition capability of MCA, the proposed method can be also extended to simultaneous implementation of face hallucination and expression normalization. Experimental results demonstrate the effectiveness of our method for the images from both lab environment and realistic scenarios. We also study the contribution of face hallucination to face recognition in the case that probe images and gallery images are under different resolutions. The main conclusion is that the contribution is significant when using local facial features (e.g., LBP), but unobvious when using holistic facial features (e.g., Eigenfaces).