Multilayer feedforward networks are universal approximators
Neural Networks
Image quilting for texture synthesis and transfer
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Space-Time Completion of Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Can Lower Resolution Be Better?
DCC '08 Proceedings of the Data Compression Conference
Generic video coding with abstraction and detail completion
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Statistical modeling and conceptualization of visual patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale curvature-based shape representation using B-spline wavelets
IEEE Transactions on Image Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
Image Completion Using Efficient Belief Propagation Via Priority Scheduling and Dynamic Pruning
IEEE Transactions on Image Processing
A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile
IEEE Transactions on Circuits and Systems for Video Technology
An encoder-decoder texture replacement method with application to content-based movie coding
IEEE Transactions on Circuits and Systems for Video Technology
Image Compression With Edge-Based Inpainting
IEEE Transactions on Circuits and Systems for Video Technology
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There is a major research effort under way to improve image and video coding efficiency through exploiting visual redundancy, in alignment with traditionally predictive coding and transform coding. It is motivated from the fact that natural images not only can be generally decomposed into texture and piecewise smooth parts called cartoon (e.g. edges), but may be recognized to consist of an overwhelming number of visual patterns generated by very diverse stochastic processes in nature. This paper explores perceptual non-parametric sampling methods into standardized video engine with structure-based prediction, and further suggests a learning-based framework for compressing image and video at low bit rate, by incorporating effective state-of-the-art inference algorithms to pursue an online synthesis solution. A crucial component is presented to learn the relationship (projection) between the abstracted patches (visual pattern) and the corresponding detail (feature space) in spatio-temporal manner. The experiment result shows the promising prospect for perceptual image and video coding.