A Three-Frame Algorithm for Estimating Two-Component Image Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Super-Resolution Reconstruction of Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extraction of high-resolution frames from video sequences
IEEE Transactions on Image Processing
An FFT-based technique for translation, rotation, and scale-invariant image registration
IEEE Transactions on Image Processing
Robust, object-based high-resolution image reconstruction from low-resolution video
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Superresolution restoration of an image sequence: adaptive filtering approach
IEEE Transactions on Image Processing
Resolution enhancement of color video sequences
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Resolution enhancement of monochrome and color video using motion compensation
IEEE Transactions on Image Processing
A recursive nonstationary MAP displacement vector field estimation algorithm
IEEE Transactions on Image Processing
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Super-resolution reconstruction algorithm produces a high-resolution image from a low-resolution image sequence. The accuracy and the stability of the motion estimation (ME) are essential for the whole restoration. In this paper, a new super-resolution reconstruction algorithm is developed using a robust ME method, which fuses multiple estimated motion vectors within the sequence. The new algorithm has two major improvements compared with the previous research. First, instead of only two frames, the whole sequence is used to obtain a more accurate and stable estimation of the motion vector of each frame; second, the reliability of the ME is quantitatively measured and introduced into the cost function of the reconstruction algorithm. The algorithm is applied to both synthetic and real sequences, and the results are presented in the paper.