Discrete-time signal processing
Discrete-time signal processing
Multiresolution sampling procedure for analysis and synthesis of texture images
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Motion Deblurring and Super-resolution from an Image Sequence
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
IEEE Transactions on Signal Processing
Extraction of high-resolution frames from video sequences
IEEE Transactions on Image Processing
Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time
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
Resolution enhancement of color video sequences
IEEE Transactions on Image Processing
A super-resolution method with EWA
Journal of Computer Science and Technology
Robust color image superresolution: an adaptive M-estimation framework
Journal on Image and Video Processing - Color in Image and Video Processing
ACM SIGGRAPH Asia 2008 papers
Region-Based Super Resolution for Video Sequences Considering Registration Error
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Analysis of multiframe super-resolution reconstruction for image anti-aliasing and deblurring
Image and Vision Computing
Understanding video sequences through super-resolution
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
Region-based weighted-norm with adaptive regularization for resolution enhancement
Digital Signal Processing
Video motion estimation with temporal coherence
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
Improving sub-pixel correspondence through upsampling
Computer Vision and Image Understanding
Wavelet-based super-resolution reconstruction: theory and algorithm
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Face hallucination based on sparse local-pixel structure
Pattern Recognition
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Reconstruction-based super-resolution from motion video has been an active area of study in computer vision and video analysis. Image alignment is a key component of super-resolution algorithms. Almost all previous super-resolution algorithms have assumed that standard methods of image alignment can provide accurate enough alignment for creating super-resolution images. However, a systematic study of the demands on accuracy of multi-image alignment and its effects on super-resolution has been lacking. Furthermore, implicitly or explicitly most algorithms have assumed that the multiple video frames or specific regions of interest are related through global parametric transformations. From previous works, it is not at all clear how super-resolution performs under alignment with piecewise parametric or local optical flow based methods. This paper is an attempt at understanding the influence of image alignment and warping errors on super-resolution. Requirements on the consistency of optical flow across multiple images are studied and it is shown that errors resulting from traditional flow algorithms may render super-resolution infeasible.