Morphological image analysis within the wavelet representation

Terrance L. Huntsberger; Bjorn D. Jawerth

doi:10.1117/12.205465

6 April 1995 Morphological image analysis within the wavelet representation

Terrance L. Huntsberger, Bjorn D. Jawerth

Proceedings Volume 2491, Wavelet Applications II; (1995) https://doi.org/10.1117/12.205465
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

Mathematical morphology, as originally described by Matheron and Serra, consists of the application of set theoretical operations between the image set X and a structure element set B. Image skeletons are very efficient representations of shape, and can be directly derived using the morphological operations of erode and open. If done at full image resolution, derivation of a skeleton can be very time consuming without dedicated signal processing hardware. This paper presents an alternative to the standard approach that relies on morphological operations within the wavelet coefficient space. In particular, the skeleton transformation can be done very efficiently at the reduced resolution of the coarse wavelet coefficient levels. We investigate the relationship between wavelet image compression and morphological transforms for the derivation of skeletons. We also report the results of some experimental studies on binary and gray scale images.

Citation Download Citation

Terrance L. Huntsberger and Bjorn D. Jawerth "Morphological image analysis within the wavelet representation", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); https://doi.org/10.1117/12.205465

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