Authors:
Hyo-Moon Cho
and
Sang-Bok Cho
Affiliation:
School of Electrical, University of Ulsan, Korea, Republic of
Keyword(s):
High resolution, Motion compensation error, Super resolution, Low resolution.
Related
Ontology
Subjects/Areas/Topics:
Image and Video Processing, Compression and Segmentation
;
Multidimensional Signal Processing
;
Multimedia
;
Multimedia Signal Processing
;
Telecommunications
Abstract:
In this paper, we introduce the input image selection-method to improve the reconstructed high-resolution (HR) image quality. To obtain ideal super-resolution (SR) reconstruction image, all input images are well-registered. However, the registration is not ideal in practice. By reason of this, the number of input images with low registration error is more important than the number of input images in order to obtain good quality of a HR image. The input image suitability could be evaluated by using statistical and restricted registration properties. Therefore, we propose the input image evaluation-method in automatic manner as pre-processing of SR reconstruction and its architecture. In video sequences, all input images in specified region are allowed to use SR reconstruction as low-resolution (LR) input image and/or the reference image. The evaluation basis is decided by the threshold value and this threshold is calculated by using the maximum motion compensation error (MMCE) of the
reference image. If the motion compensation error (MCE) of LR input image is in the range of 0 < MCE < MMCE then this LR input image is selected for SR reconstruction, else then LR input image are neglected. The optimal reference LR (ORLR) image is decided by comparing the number of the selected LR input (SLRI) images for each reference LR input (RLRI) image. Finally, we generate a HR image by using optimal reference LR image and selected LR images and by using the Hardie’s interpolation method. This proposed algorithm is expected to improve the quality of SR without any user intervention.
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