Overview of adaptive morphology: Trends and perspectives

Abstract

In this paper we briefly overview emerging trends in 'Adaptive Morphology', i.e. work related to the theory and/or applications of image analysis filters, systems, or algorithms based on mathematical morphology, that are adaptive w.r.t. to space or intensity or use any other adaptive scheme. We present a new classification of work in this area structured along several major theoretical perspectives. We then sample specific approaches that develop spatially-variant structuring elements or intensity level-adaptive operators, modeled and implemented either via conventional nonlinear digital filtering or via geometric PDEs. Finally, we discuss some applications.

Multiscale Image Analysis Based on Robust and Adaptive Morphological Scale-Spaces

“…For an overview on the state-the-art on adaptive morphology, the interested reader is invited to the paper Maragos and Vachier (2009) and the most recent one (Ćurić et al, 2014). Another milestone study (Roerdink, 2009) is very interesting for understanding the theoretical limitations of inputadaptive morphological operators.…”

An Approach to Adaptive Quadratic Structuring Functions Based on the Local Structure Tensor

“…This has led to the development of adaptive mathematical morphology, where the structuring element (in the adaptive case often called structuring function) may change for each point in the image. For a review of the field of adaptive mathematical morphology, the interested reader is referred to [9] and [14].…”

Patch-Based Mathematical Morphology for Image Processing, Segmentation and Classification

“…With the need of more efficient morphological image processing operators, there has been recently much interest in the development of adaptive mathematical morphology (see [8] for a recent survey). Roughly, two types of adaptive MM can be considered [17,8,14]: i) location-adaptive MM: the shape of the structuring element depends on the location x in the image, ii) input-adaptive MM: the shape of the structuring element depends on local features extracted at the location x. In the same time, image processing using local patches has become very popular and was shown to be highly effective [6].…”