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Fast and robust image processing algorithms based on approximations to order statistics

机译：基于阶数统计近似的快速而强大的图像处理算法

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A test system with four cameras in the infrared and visual spectra is under development at FFI (The Norwegian Defence Research Establishment). The system can be mounted on a high speed jet aircraft, but may also be used in a land-based version. It can be used for image acquisition as well as for development and test of automatic target recognition (ATR) algorithms. The sensors on board generate large amounts of data, and the scene may be rather cluttered or include anomalies (e.g. sun glare). This means we need image processing and pattern recognition algorithms which are robust, fast (real-time), and able to handle complex scenes. Algorithms based on order statistics are known to be robust and reliable. However, they are in general computationally heavy, and thus often unsuitable for real time applications. But approximations to order statistics do exist. Median of medians is one example. This is a technique where an approximation of the median of a sequence is found by first dividing the sequence in subsequences, and then calculating median (of medians) recursively. The algorithm is very efficient, the processing time is of order O(n). By utilizing such techniques for estimating image statistics, the computational challenge can be overcome. In this paper we present strategies for how approximations to order statistics can be applied for developing robust and fast algorithms for image processing, especially visualization and segmentation.
机译：FFI（挪威国防研究机构）正在开发一种在红外和可见光谱中具有四台摄像机的测试系统。该系统可以安装在高速喷气飞机上，但也可以用于陆基版本。它可用于图像采集以及自动目标识别（ATR）算法的开发和测试。机载传感器会生成大量数据，并且场景可能会很杂乱或包含异常情况（例如，眩光）。这意味着我们需要强大，快速（实时）并且能够处理复杂场景的图像处理和模式识别算法。已知基于顺序统计的算法是健壮且可靠的。但是，它们通常计算量很大，因此通常不适合实时应用。但是确实存在阶数统计的近似值。中位数的中位数是一个示例。这是一种通过先将序列划分为子序列，然后递归计算（中位数）中位数来找到序列中位数的近似值的技术。该算法非常有效，处理时间约为O（n）。通过利用这样的技术来估计图像统计量，可以克服计算上的挑战。在本文中，我们提出了如何将阶次统计量的近似值应用于开发鲁棒且快速的图像处理算法（尤其是可视化和分段）的策略。

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