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Super-resolution reconstruction of video sequences based on wavelet-domain spatial and temporal processing

机译:基于小波域时空处理的视频序列超分辨率重构

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Super-resolution (SR) have gained increasing attention recently, especially in the fields of medical images, satellite images, and video surveillance applications. It is our focus to explore the SR techniques for videos containing diverse kinds of motions (global or local motions). To this aim, we adopt the strategy of wavelet-domain processing, focusing on the estimation of high-frequency (LH, HL, and HH bands) wavelet coefficients from both the spatial and temporal information. The detail wavelet coefficients are estimated from the reference frame by performing weighted motion compensation in the wavelet domain, which is then fused with those obtained from Lanczos interpolation of the current frame. Experiments show that our algorithm outperforms traditional interpolation methods by 1.0dB ∼ 2.2dB in reconstruction PSNR within reasonable computing time.
机译:最近,超分辨率(SR)受到越来越多的关注,特别是在医学图像,卫星图像和视频监视应用领域。探索包含各种动作(全局或局部动作)的视频的SR技术是我们的重点。为此,我们采用小波域处理策略,着重于从时空信息估计高频(LH,HL和HH频带)小波系数。通过在小波域中执行加权运动补偿,可以从参考帧估计细节小波系数,然后将其与从当前帧的Lanczos插值获得的小波系数融合。实验表明,在合理的计算时间内,该算法在重建PSNR方面优于传统的内插方法1.0dB〜2.2dB。

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