Intensity image quality assessment based on multiscale gradient magnitude similarity deviation
| Autor: | Shiwei Chen, Yueping Huang, Xiaogang Yang, Naixin Qi, Xiaofeng Li |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Image quality media_common.quotation_subject General Engineering Image processing Pattern recognition Atomic and Molecular Physics and Optics Contourlet Intensity (physics) Speckle pattern Human visual system model Contrast (vision) Noise (video) Artificial intelligence business media_common |
| Zdroj: | Optical Engineering. 59 |
| ISSN: | 0091-3286 |
| DOI: | 10.1117/1.oe.59.10.103107 |
| Popis: | Laser active imaging is widely used in many fields. The intensity image quality of laser active imaging is affected by various degradations, such as speckle effect and noise. Most existing objective image quality assessment (IQA) methods that consider only a single distorted image are not suitable for an intensity image. A multiscale full-reference intensity IQA method is presented. The proposed method is based on an improved gradient magnitude similarity deviation (GMSD) in the nonsubsampled contourlet transform (NSCT) domain. The reference and distorted images are decomposed by NSCT to emulate the multichannel structure of the human visual system. Then, the GMSD of each sub-band is computed to capture the intensity image quality. At last, the contrast sensitivity function implementation is employed in the sub-bands of the NSCT domain. All sub-bands’ GMSD is evaluated and pooled together to yield the objective quality index of a distorted intensity image. Experimental results show that the proposed method can effectively and accurately evaluate the quality of intensity images, and it is highly consistent with subjective perception. |
| Databáze: | OpenAIRE |
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