Topological Data Analysis For Evaluating PDE-based Denoising Models
| Autor: | Ehsan M. Hameed, Ahmed K. Al-Jaberi |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 1897:012006 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/1897/1/012006 |
| Popis: | Image denoising is process of removing the noise (i.e. artifacts) in digital image. Noise reduction is an essential process of image processing in order to improve, analyze and interpret important information in an image. Edges are important to the visual appearance of images, to preserve important features such as edges and corners during the noise reduction process. A class of fourth- and second-order partial differential equations (PDEs) are used to optimize the trade-off between noise removal and edge preservation. Image quality assessment plays an important role in various image processing applications. It is still an active field of research. Several techniques have been suggested for measuring image quality but none of them are ideal for measuring the quality. This paper presents a new assessment of image quality based on topological data analysis (TDA) which is used for evaluating noise removal from colour images and also for assessing the performance of PDE-based denoising models. The experimental results show that the proposed assessment model gives high correlation. Furthermore, the proposed method provides very low computational load and similar extraction of characteristics to human perceptional assessment. |
| Databáze: | OpenAIRE |
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