COMPARATIVE STUDY OF THE DIFFERENT VERSIONS OF THE GENERAL IMAGE QUALITY EQUATION
| Autor: | A. Q. Valenzuela, J. C. G. Reyes |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
lcsh:Applied optics. Photonics
Computer science Image quality lcsh:T 010401 analytical chemistry 0211 other engineering and technologies lcsh:TA1501-1820 Image processing 02 engineering and technology Classification of discontinuities computer.software_genre 01 natural sciences lcsh:Technology 0104 chemical sciences Image (mathematics) Signal-to-noise ratio lcsh:TA1-2040 Metric (mathematics) NIIRS Data mining lcsh:Engineering (General). Civil engineering (General) computer 021101 geological & geomatics engineering Interpretability |
| Zdroj: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-2-W5, Pp 493-500 (2019) |
| ISSN: | 2194-9050 2194-9042 |
| Popis: | The General Image Quality Equation (GIQE) is an analytical tool derived by regression modelling that is routinely employed to gauge the interpretability of raw and processed images, computing the most popular quantitative metric to evaluate image quality; the National Image Interpretability Rating Scale (NIIRS). There are three known versions of this equation; GIQE3, GIQE4 and GIQE5, but the last one is scarcely known. The variety of versions, their subtleties, discontinuities and incongruences, generate confusion and problems among users. The first objective of this paper is to identify typical sources of confusion in the use of the GIQE, suggesting novel solutions to the main problems found in its application and presenting the derivation of a continuous form of GIQE4, denominated GIQE4C, that provides better correlation with GIQE3 and GIQE5. The second objective of this paper is to compare the predictions of GIQE4C and GIQE5, regarding the maximum image quality rating that can be achieved by image processing techniques. It is concluded that the transition from GIQE4 to GIQE5 is a major paradigm shift in image quality metrics, because it reduces the benefit of image processing techniques and enhances the importance of the raw image and its signal to noise ratio. |
| Databáze: | OpenAIRE |
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