Title: | Sharpness Measurement by Edge-related Frequency Components |
Authors: | Lee, Yuan-Kang Ding, Jian-Jiun |
Citation: | WSCG 2024: full papers proceedings: 32. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 371-376. |
Issue Date: | 2024 |
Publisher: | Václav Skala - UNION Agency |
Document type: | konferenční příspěvek conferenceObject |
URI: | http://hdl.handle.net/11025/57411 |
ISSN: | 2464–4625 (online) 2464–4617 (print) |
Keywords: | ostrost obrazu;rozmazání obrazu;bez odkazu;oddělená vlnková transformace;detekce hrany;hodnocení kvality obrazu |
Keywords in different language: | image sharpness;image blur;no-reference;discrete wavelet transform;edge detection;image quality assessment |
Abstract in different language: | In this paper, a novel no-reference image quality metric of sharpness is proposed. Our image quality metric is evaluated on two key attributes discerned during the assessment of image sharpness by the human visual system (HVS): 1. Image sharpness is principally contingent upon the salience of edges within the image. 2. With an increase in the decomposition level of the Discrete Wavelet Transform (DWT), the high-frequency coefficients correspond to higher spatial frequency information in an image. Experimental results show that in comparison to other state-of-the-art metrics, our method not only accurately assesses image sharpness in both defocus and motion blur scenarios but also showcases superior precision and broader applicability. |
Rights: | © Václav Skala - UNION Agency |
Appears in Collections: | WSCG 2024: Full Papers Proceedings |
Files in This Item:
File | Description | Size | Format | |
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A11-2024.pdf | Plný text | 1,52 MB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/57411
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