Temporal Super Resolution from a Single Quasi-periodic Image Sequence Based on Phase Registration
نویسندگان
چکیده
This paper describes a method for temporal super resolution from a single quasi-periodic image sequence. A so-called reconstructionbased method is applied to construct a one period image sequence with high frame-rate based on phase registration data in sub-frame order among multiple periods of the image sequence. First, the periodic image sequence to be reconstructed is expressed as a manifold in the parametric eigenspace of the phase. Given an input image sequence, phase registration and manifold reconstruction are alternately executed iteratively within an energy minimization framework that considers data fitness and the smoothness of both the manifold and the phase evolution. The energy minimization problem is solved through three-step coarse-to-fine procedures to avoid local minima. The experiments using both simulated and real data confirm the realization of temporal super resolution from a single image sequence.
منابع مشابه
Periodic Temporal Super Resolution Based on Phase Registration and Manifold Reconstruction
This paper describes a method for periodic temporal super resolution, namely, reconstructing a one period image sequence with high frame-rate from a single quasi-periodic image sequence with low frame-rate. First, the periodic image sequence to be reconstructed is expressed as a manifold in the parametric eigenspace of the phase, namely, period-normalized time. Given an input image sequence, ph...
متن کاملRobust Fuzzy Content Based Regularization Technique in Super Resolution Imaging
Super-resolution (SR) aims to overcome the ill-posed conditions of image acquisition. SR facilitates scene recognition from low-resolution image(s). Generally assumes that high and low resolution images share similar intrinsic geometries. Various approaches have tried to aggregate the informative details of multiple low-resolution images into a high-resolution one. In this paper, we present a n...
متن کاملA Deep Model for Super-resolution Enhancement from a Single Image
This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model benefits from high frequency and low frequency features extracted from deep and shallow networks...
متن کاملMulti-frame Super Resolution for Improving Vehicle Licence Plate Recognition
License plate recognition (LPR) by digital image processing, which is widely used in traffic monitor and control, is one of the most important goals in Intelligent Transportation System (ITS). In real ITS, the resolution of input images are not very high since technology challenges and cost of high resolution cameras. However, when the license plate image is taken at low resolution, the license...
متن کاملEffective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction
Purpose: Probe-based Confocal Laser Endomicroscopy (pCLE) is a recent imaging modality that allows performing in vivo optical biopsies. The design of pCLE hardware, and its reliance on an optical fibre bundle, fundamentally limits the image quality with a few tens of thousands fibres, each acting as the equivalent of a single-pixel detector, assembled into a single fibre bundle. Video-registrat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010