Reconstruction of Partially Damaged Face Images Based on a Morphable Face Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Cross-Type Peak-and-Valley Filter for Error Prevention and Resilience in Image Communications
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Face Reconstruction from Partial Information Based on a Morphable Face Model
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Parallel VLSI design for a real-time video-impulse noise-reduction processor
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A Variational Approach to Remove Outliers and Impulse Noise
Journal of Mathematical Imaging and Vision
Resolution enhancement of facial image based on top-down learning
IWVS '03 First ACM SIGMM international workshop on Video surveillance
Joint cross-layer design for wireless QoS video delivery
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Segmentation of ultrasound liver images: an automatic approach
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Efficient impulse noise reduction via local directional gradients and fuzzy logic
Fuzzy Sets and Systems
Salt and Pepper Noise Removal from Document Images
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
A novel evolutionary approach to image enhancement filter design: method and applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A fast efficient restoration algorithm for high-noise image filtering with adaptive approach
Journal of Visual Communication and Image Representation
Synthesis of high-resolution facial image based on top-down learning
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Switching bilateral filter with a texture/noise detector for universal noise removal
IEEE Transactions on Image Processing
Resolution enhancement of facial image using an error back-projection of example-based learning
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A fuzzy filter for the removal of random impulse noise in image sequences
Image and Vision Computing
Automated liver detection in ultrasound images
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Evolutionary image enhancement for impulsive noise reduction
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Stepwise reconstruction of high-resolution facial image based on interpolated morphable face model
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
How can we reconstruct facial image from partially occluded or low-resolution one?
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
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A generic n-dimensional filter with the primary purpose of eliminating impulsive-like noise is presented. This recursive nonlinear filter is composed of two conditional rules, which are applied independently, in any order, one after the other. It identifies noisy items by inspection of their surrounding neighborhood, and afterwards it replaces their values with the most “conservative” ones out of their neighbors' values. In this way, no new values are introduced and the histogram distribution range is conserved. This n-dimensional filter can be decomposed recursively to a lower dimensional space, each time generating two sets of n(n-1)-dimensional filters. This study, which focuses on the case of two-dimensional signals (gray scale images), explores one possible implementation of this new filter and orients the evaluation of its performance toward the median filter, as this filter is the basis of many more sophisticated filters for impulsive noise reduction. Tests were carried out using both real and artificial images. We found this new filter to be much faster than the median filter while performing comparably in terms of both image information conservation and noise reduction, which suggests that it could replace the median filter for the preliminary processing included in state-of-the-art noise removal filters. This new filter should either eliminate or attenuate most noisy pixels in synthetic and natural images not excessively contaminated. It has a slight smoothing effect on nonnoisy image regions. In addition, it is scalable, easily implemented, and adaptable to specific applications