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Real-time restoration of images degraded by uniform motion blur in foveal active vision systems

机译:中央凹主动视觉系统中由于均匀运动模糊而退化的图像的实时恢复

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Foveated, log-polar, or space-variant image architectures provide a high resolution and wide field workspace, while providing a small pixel computation load. These characteristics are ideal for mobile robotic and active vision applications, but have been little used due to the general lack of image processing tools that are applicable to the log-polar coordinate system. Recently, we have described a generalization of the Fourier transform (the fast exponential chirp transform), which allows frame-rate computation of full-field two-dimensional (2-D) frequency transforms directly in log-polar coordinates. In the present work, we show that is possible to achieve full-frame image de-blur at frame rate on a standard "PC" platform, using these methods, we illustrate this idea with a Wiener filter based restoration technique. The main contribution of this note is the implementation of (space-variant) image de-blur directly in log-polar coordinates, using the exponential chirp transform. The results show reasonable quality of de-blur, and suggest that these methods are relevant to applications in mobile image processing platforms in which real-time motion deblur is important, and for which it is not desirable to use extensive or custom fabricated hardware.
机译:凹面,对数极性或空间变化的图像体系结构可提供高分辨率和宽视场工作空间,同时提供较小的像素计算负担。这些特性非常适合移动机器人和主动视觉应用,但由于普遍缺乏适用于对数极坐标系统的图像处理工具,因此很少使用。最近,我们描述了傅立叶变换(快速指数线性调频变换)的一般化,它允许直接在对数极坐标中对全场二维(2-D)频率变换进行帧速率计算。在当前的工作中,我们展示了使用这些方法在标准“ PC”平台上以帧速率实现全帧图像去模糊的可能性,并使用基于Wiener滤波器的还原技术说明了这一思想。该注释的主要贡献是使用指数线性调频变换直接在对数极坐标中实现了(空间变量)图像去模糊。结果显示了合理的去模糊质量,并表明这些方法与移动图像处理平台中的应用有关,在该应用中,实时运动去模糊很重要,并且不希望使用大量的或定制的硬件。

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