Special Issue "Advances on Clustering Algorithms for Image Processing"
Deadline for manuscript submissions: closed (30 September 2020).
Interests: clustering; machine learning; data mining; location-based applications
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Clustering methods have been actively developed for decades for applications in databases, data analysis, web mining, recognition systems, pattern recognition, and also image processing. Clustering depends on two things: Objective function such as sum-of-squared errors (SSE), and the algorithm that tries to optimize this function.
Simple algorithms like k-means are still widely used. Recent results have shown that with change of the initialization technique and by repeating the algorithm 100 times, one can reduce the error so that the algorithm is well suited for most pattern recognition applications. Some other applications may require more accurate clustering, and better methods like random swap are needed. These techniques can be evaluated on benchmarking datasets.
An open question is to what extent these results apply to clustering for image processing. What clustering algorithm and which objective function should be used in remote sensing? It is expected that the role of the algorithm is less critical in image processing, and the choice of the features and objective function are more important in the clustering. In image segmentation, a simple extension of k-means adds the pixel location (x,y) to the color value (r,g,b) and then uses the existing clustering methods.
The number of clusters should also be solved. A common approach is to use the heuristic merge-based criterion, which effectively leads to agglomerative clustering with the stopping criterion. An open question is whether cluster validity indexes can be applied instead of the heuristic criterion.
This call for papers invites submissions of new methods and review papers that study how clustering methods are effectively applied in image processing. The application can be image enhancement, filtering, segmentation, object extraction or any other process that is used in remote sensing. Review papers based on systematic comparison of single components are especially welcome.
Prof. Pasi Fränti
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Image processing
- Satellite images