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Review of image similarity measures for joint image reconstruction from multiple measurements. (English) Zbl 1487.65138

Kaltenbacher, Barbara (ed.) et al., Time-dependent problems in imaging and parameter identification. Cham: Springer. 267-286 (2021).
Summary: It is fundamental in image processing how to measure image similarity quantitatively for tasks such as image quality assessment, image registration, image reconstruction from multiple measurements, etc.. An image similarity measure (ISM) is both task-dependent and feature-dependent, and must be designed according to the characteristics of specific tasks and features. Simply applying distances from the mathematical metric theory or general divergences to spaces of images or spaces of image features usually does not provide appropriate ISMs. In this chapter, we review several ISMs for image reconstruction problems from multiple measurements of various types in recent work. The multiple measurements considered here include multi-modality, multi-spectral, and multi-temporal measurements, with multi-modality tomography, multi-spectral XCT, and dynamic tomography, as the imaging applications, respectively. We focus on motivations and constructions of the ISMs and avoid their general rigorous mathematical presentations to simplify notations for the readability for a general audience. ISMs under review are proposed for image structural similarity and have been successfully applied to image reconstruction from multiple measurements.
For the entire collection see [Zbl 1471.65006].

MSC:

65M32 Numerical methods for inverse problems for initial value and initial-boundary value problems involving PDEs
65K10 Numerical optimization and variational techniques
78A46 Inverse problems (including inverse scattering) in optics and electromagnetic theory
92C55 Biomedical imaging and signal processing
94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
35R30 Inverse problems for PDEs
Full Text: DOI

References:

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