Soft morphological image resizing

Pavel A. Maltseff

doi:10.1117/12.271137

4 April 1997 Soft morphological image resizing

Pavel A. Maltseff

Proceedings Volume 3026, Nonlinear Image Processing VIII; (1997) https://doi.org/10.1117/12.271137
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

Abstract

One important problem in computer vision and image processing is image resizing. Current techniques are generally based on different interpolation methods. These methods are convenient but the downsampled or upsampled image will include new gray values which are not present in the original image. Soft morphological interpolation is a new technique for resampling discrete data. The soft morphological operations are an alternative to the standard morphological operation. The generic description of hierarchical soft morphological transformations was done previously. The further development of soft morphological operations by a hierarchical structural system uses the relaxation of the requirement that the result of the operation must be the r-th largest or smallest value of the corresponding multiset, where r is an order index of the internal hard center. We will assume that any reasonable integer value is acceptable. The purpose of this paper is to derive the sot morphological convolution and compare the result of this convolution with the cubic convolution and Gaussian pyramid.

Citation Download Citation

Pavel A. Maltseff "Soft morphological image resizing", Proc. SPIE 3026, Nonlinear Image Processing VIII, (4 April 1997); https://doi.org/10.1117/12.271137

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KEYWORDS

Convolution

Image processing

Digital filtering

Computer vision technology

Image compression

Machine vision

Transform theory

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