Fast Implementation Of Ranked Filters On General-Purpose Image Processing Hardware

Frederick M. Waltz

doi:10.1117/12.948968

21 March 1989 Fast Implementation Of Ranked Filters On General-Purpose Image Processing Hardware

Frederick M. Waltz

Proceedings Volume 1004, Automated Inspection and High-Speed Vision Architectures II; (1989) https://doi.org/10.1117/12.948968
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

The median filter is one widely-used member of the class of ranked-intensity filters. Such filters are useful in signal processing, and particularly in machine vision, because they effectively remove an important and difficult-to-deal-with kind of noise, called variously "spike" noise or "salt-and-pepper" noise. By their nature, these filters are nonlinear. Filters involving linear operations, such as convolution - a weighted summation of the pixels in a neighborhood - can be done incrementally, and hence lend themselves to implementation on fast "pipelined" architectures. Two special cases of ranked-intensity filters, the "maximum" and "minimum" filters, can also be implemented incrementally. In contrast, the general ranked-intensity filter requires a sorting process over all pixels in the neighborhood. The usual "bubble sort" algorithm requires n passes and n*(n-1)/2 separate comparisons to fully determine the rank of all pixels in an n-pixel neighborhood. More efficient algorithms are known, but these also require multiple passes. As a result, software implementations of ranked-intensity filters are slow, and the hardware implementations now becoming available require special boards or chips devoted to that function alone. This paper presents improved sorting algorithms for ranked-intensity filters, and shows various practical techniques for implementation of these algorithms on existing fast multi-purpose image processing hardware. While not as fast as a dedicated hardware implementation, the resulting system is considerably faster than a software implementation, and yet it retains the general-purpose character of software systems. This makes it useful for laboratory algorithm development systems and for near-real-time applications. The same algorithms could also be used to design more efficient custom hardware or provide faster software implementations.

Citation Download Citation

Frederick M. Waltz "Fast Implementation Of Ranked Filters On General-Purpose Image Processing Hardware", Proc. SPIE 1004, Automated Inspection and High-Speed Vision Architectures II, (21 March 1989); https://doi.org/10.1117/12.948968

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