Image quality assessment (IQA) using high-frequency and image variance (HFIV) for colour image

Image quality is often lost during image acquisition, transmission, and compression. Therefore, image quality assessment (IQA) is crucial in image processing. Currently, image quality can be measured from the frequency domain features, but it only applicable to blurred grayscale images. Nevertheless...

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Bibliographic Details
Published in:Journal of physics. Conference series 2019-11, Vol.1372 (1), p.12034
Main Authors: Tan, Li Chien, Yazid, Haniza, Chong, Yen Fook
Format: Article
Language:English
Subjects:
Color
Compression tests
Digital imaging
Distortion
Image acquisition
Image compression
Image enhancement
Image processing
Image quality
Image transmission
Noise
Physics
Quality assessment
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Description
Summary:Image quality is often lost during image acquisition, transmission, and compression. Therefore, image quality assessment (IQA) is crucial in image processing. Currently, image quality can be measured from the frequency domain features, but it only applicable to blurred grayscale images. Nevertheless, noise distortion is also a common problem in digital images, and colour also affects the perception of image quality. Therefore, this paper proposes an enhanced blur and noise specific colour image quality assessment that measures high-frequency components and image variance. The number of high-frequency components is related to the edge and noise. In order to distinguish the distortion of the image, the image variance estimation is included. Experiments on public databases have shown that this method outperforms PSNR and SSIM in terms of noise and blur distortion and has low processing time of 0.0941 s/img.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1372/1/012034