Separating Low Pass and High Pass Frequencies in the Image Without loosing information
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Copyright: © 2020 Z. Alqadi, J. Musbah and A. L. Montengro. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Granulometries are morphological image analysis tools that are particularly useful for estimating object sizes in binary and grayscale images, or for characterizing textures based on their pattern spectra. There are many applications that morphology can be applied to. Some morphological operations like dilation, erosion and open-close are used in image and video processing, but with no application to pre-processing for increasing a Codec's performance. These operations can be used as filters and if applied on an image, some information will be lost. In order to avoid information loose a sequence of morphological operation is suggested, this sequence can be used to separate low pass and high pass frequencies from the image without throwing any piece of data and the original image can always be reconstructed.
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- gray-level morphology