Abstract
Abstract This paper presents a resolution enhancement algorithm in an asymmetric resolution stereo video for improving the video resolution. In this stereo video architecture, a scene is captured by two cameras to form two views, one view is a lower-resolution video and the other is a full-resolution video. The goal is to enhance the lower-resolution video to a full-resolution video. In the lower-resolution video, frames synchronized with full-resolution video are enhanced via disparity estimation algorithm, while the rest frames are improved by mono-view video super-resolution based on key frames method. The experimental results demonstrate that the proposed method is effective for both visual and objective qualities.
Highlights
Nowadays, with the development of image/video processing techniques and display techniques, high resolution and quality videos become more widespread than 20 years ago
The computational complexity is according to the whole resolution enhancement algorithm
In the stage of synchronized frames enhancement, disparity estimation is pixel-based; the computational complexity of this stage is proportional to the size of resolution basically
Summary
With the development of image/video processing techniques and display techniques, high resolution and quality videos become more widespread than 20 years ago. It is a process to create a high-resolution (HR) video sequence from a low-resolution (LR) video sequence, which is applying high correlation between mono-view LR frames to extract effective information for the compensation. Video super-resolution algorithms are ubiquitously used for mono-view video enhancement [1,2,3,4,5,6,7,8]. Brandi et al had a superresolution algorithm for the mixed resolution framework [6]. He had set the HR frames as the key frames and treated the LR frames as non-key frames; he improved the resolution of non-key frames by key frames information. Najafi et al [11] used HR frames to form a regularization function and used it for super-resolution de-blurring stage
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