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首页> 外文会议>Conference on Image Processing: Algorithms and Systems III; 20040119-20040121; San Jose,CA; US >Minimal-memory bit vector architecture for computational mathematical morphology
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Minimal-memory bit vector architecture for computational mathematical morphology

机译：用于计算数学形态学的最小内存位向量架构

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摘要

Computational mathematical morphology (CMM) is a nonlinear filter representation particularly amenable to real-time image processing. In the state of the art implementation each pixel value in a windowed observation is indexed into a separate lookup table to retrieve a set of bit vectors. Each bit in the vector corresponds to a basis element in the CMM filter representation. All retrieved bit vectors are "anded" together to produce a bit vector with a unique nonzero bit. The position of that bit corresponds to a basis element containing the observation and it used to look up a filter value in a table. The number of stored bit vectors is a linear function of the image or signal bit depth. We present an architecture for CMM implementation that uses a minimal number of bit vectors and required memory is less sensitive to bit depth. In the proposed architecture, basis elements are projected to subspaces and only bit vectors unique to each subspace are stored. With the addition of an intermediate lookup table to map observations to unique bit vectors, filter memory is greatly reduced. Simulations show that the architecture provides an advantage for random tessellations of the observation space. A 50% memory savings is shown for a practical application to digital darkness control in electronic printing.
机译：计算数学形态学（CMM）是一种非线性滤波器表示形式，特别适合于实时图像处理。在现有技术的实现中，窗口观察中的每个像素值被索引到单独的查找表中以检索一组位向量。向量中的每个位对应于CMM过滤器表示形式中的基本元素。将所有检索到的位向量“与”在一起，以产生具有唯一非零位的位向量。该位的位置对应于包含观察值的基础元素，它用于在表中查找过滤器值。所存储的位向量的数量是图像或信号位深度的线性函数。我们提出了一种用于CMM实现的体系结构，该体系结构使用最少数量的位向量，并且所需的内存对位深度不那么敏感。在提出的体系结构中，基本元素被投影到子空间，并且仅存储每个子空间唯一的位向量。通过添加中间查找表将观察结果映射到唯一的位向量，可以大大减少过滤器的内存。仿真表明，该架构为观察空间的随机镶嵌提供了优势。对于电子打印中的数字暗度控制的实际应用，显示了50％的内存节省。

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