基于内容的视频图像非线性缩放技术研究
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摘要
近年来,提升LED显示屏的播放质量已经成为业内的研究热点。用户在定制LED显示屏时,拥有很高的灵活度,可以自由选择屏幕的尺寸和宽高比。如果屏幕不符合标准比例,则全屏播放视频时,就会产生失真现象。在这种情况下,如何提高显示质量就成为急需解决的问题。
本文的设计方法,可以在一定程度上解决这一难题。
作者首先寻找图像中的视觉焦点区域。提出了一种改进的Canny自适应边缘检测算法。改进后的算法,不仅不需要人工输入参数,而且在处理含有噪声的图像时,也能取得良好效果。接下来,又对提取的边缘图进行消除杂散边处理。这样做,可以大幅降低后续图像分割的压力。
非线性缩放可以看做是等比例的缩放以及非等比例拉伸的组合。而拉伸方向一般是一维空间的。根据这个特点,作者提出了一种简单有效的图像分割算法。该方法能够根据边缘点沿拉伸方向的投影分布情况,迅速把图像分解为背景区域和含目标区域。实验证明,该算方法不仅有效,而且执行时间在整个算法实现过程中,可以忽略不计。
由于背景区域的放大倍数会大于目标区域,为了避免由于拉伸比例过大,而出现的视觉抽丝现象。作者提出了基于放大倍数的虚拟与插值相结合的背景放大方法。实验表明,该方法在特定图像中,可以取得良好的效果。
最后,作者采用GPU并行加速技术以满足实时性要求,采用DirectShow视频处理框架实现对视频当前帧的提取。
In recent years, to enhance the display quality of LED panel has become a research hotspot in the industry. The screen size and aspect ratio of LED panel is free to choose by users. It will be distortion, if the screen does not meet the standard ratios in a full-screen play. In this case, how to improve the display quality has become urgent to be solved. The methods in this paper can solve this problem to some extent.
First, the author finds the visual focus region of image. It is proposed an improved adaptive Canny algorithm. The improved algorithm, not only do not need to manually input parameters, but also can achieve good results when dealing with noisy images. Then, it has suppressed the stray edges from edge image. To do this, it can significantly reduce the pressure of the following image segmentation.
Non-linear scaling can be seen as a proportional scaling and non-proportional tensile combination. And the tensile direction is always along with one-dimensional space. Based on this characteristic, the author has proposed a simple and effective algorithm for image segmentation. This method is edge points projection based, and it can rapidly segment the image as backgrounds and foregrounds. Experiments have proved that this method is not only effective but also very fast.
The amplification of background region would be greater than the foreground area. In order to avoid the phenomenon of visual snag when the stretch ratio is too large, the author has proposed a background scaling method which is based on the combination of background virtualization and interpolation amplification. Experiments have proved that it can achieve good results in some images.
Finally, the author has used a parallel GPU acceleration technology to meet the real-time requirements, and used DirectShow framework to process the video frames.
本文的设计方法,可以在一定程度上解决这一难题。
作者首先寻找图像中的视觉焦点区域。提出了一种改进的Canny自适应边缘检测算法。改进后的算法,不仅不需要人工输入参数,而且在处理含有噪声的图像时,也能取得良好效果。接下来,又对提取的边缘图进行消除杂散边处理。这样做,可以大幅降低后续图像分割的压力。
非线性缩放可以看做是等比例的缩放以及非等比例拉伸的组合。而拉伸方向一般是一维空间的。根据这个特点,作者提出了一种简单有效的图像分割算法。该方法能够根据边缘点沿拉伸方向的投影分布情况,迅速把图像分解为背景区域和含目标区域。实验证明,该算方法不仅有效,而且执行时间在整个算法实现过程中,可以忽略不计。
由于背景区域的放大倍数会大于目标区域,为了避免由于拉伸比例过大,而出现的视觉抽丝现象。作者提出了基于放大倍数的虚拟与插值相结合的背景放大方法。实验表明,该方法在特定图像中,可以取得良好的效果。
最后,作者采用GPU并行加速技术以满足实时性要求,采用DirectShow视频处理框架实现对视频当前帧的提取。
In recent years, to enhance the display quality of LED panel has become a research hotspot in the industry. The screen size and aspect ratio of LED panel is free to choose by users. It will be distortion, if the screen does not meet the standard ratios in a full-screen play. In this case, how to improve the display quality has become urgent to be solved. The methods in this paper can solve this problem to some extent.
First, the author finds the visual focus region of image. It is proposed an improved adaptive Canny algorithm. The improved algorithm, not only do not need to manually input parameters, but also can achieve good results when dealing with noisy images. Then, it has suppressed the stray edges from edge image. To do this, it can significantly reduce the pressure of the following image segmentation.
Non-linear scaling can be seen as a proportional scaling and non-proportional tensile combination. And the tensile direction is always along with one-dimensional space. Based on this characteristic, the author has proposed a simple and effective algorithm for image segmentation. This method is edge points projection based, and it can rapidly segment the image as backgrounds and foregrounds. Experiments have proved that this method is not only effective but also very fast.
The amplification of background region would be greater than the foreground area. In order to avoid the phenomenon of visual snag when the stretch ratio is too large, the author has proposed a background scaling method which is based on the combination of background virtualization and interpolation amplification. Experiments have proved that it can achieve good results in some images.
Finally, the author has used a parallel GPU acceleration technology to meet the real-time requirements, and used DirectShow framework to process the video frames.
引文
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