Mathematical modelling serves as a framework for defining many image and signal processing problems in literature. The design of an appropriate mathematical model simplifies the overall analysis and improves the accuracy and robustness of the processing task at hand. There are quite a few mathematical techniques which are scalable, extendable and tuneable to be suited to some of the well-known image and signal processing problems. We will focus on various mathematical frameworks for defining and solving the well-known problems in image and signal processing.
Designing a suitable mathematical model helps in deriving the theoretical aspects of the problem, like stability, convergence, existence and the uniqueness of the solution. Further the verification of the model in terms of these parameters (in theoretical sense) helps in designing a robust experimental setup to test and validate them. This special issue will be a good reference for the researchers working in the area of mathematical image and signal processing. All recent and relevant techniques with regard to the topic will be explored.
Suitable topics include, but are not limited to, the following:
- Variational methods for image and signal processing
- PDE based image and signal processing
- Wavelet models for image processing
- Stochastic models for images and signals
- Fast numerical algorithms for image processing
- Image and signal reconstruction
- Mathematical morphology
- Image compression
- Image registration, in-painting and analysis
- Mathematical models in imaging (viz. medical, satellite etc.) applications
Important Dates
Submission of manuscripts: 31 December, 2016
Notification to authors: 30 April, 2017
Final versions due: 30 June, 2017
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