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Greyscale morphology is more efficient and useful for processing greyscale image. It is the extension of binary morphology by use of a min or max operations. Optics is suitable for the implementation of morphological transformations because of its parallelism. However, greyscale morphology with both greyscale images and greyscale structuring elements is difficult to realize threshold decomposition since it does not commute with threshold. We propose a correlation approach for greyscale morphological transformations using area-coding technique to represent the umbra of surfaces of both greyscale image and greyscale structuring element. A primary experiment of greyscale dilation is presented.
Greyscale morphology is more efficient and useful for processing greyscale image. It is the extension of binary morphology by use of a min or max operations. Optics is suitable for the implementation of morphological transformations because of its parallelism. However, greyscale morphology with both greyscalecale images and greyscale structuring elements is difficult to realize threshold decomposition since it does not commute with threshold. We propose a correlation approach for greyscale morphological transformations using area-coding technique to represent the umbra of surfaces of both greyscale image and greyscale structuring element. A primary experiment of greyscale dilation is presented.