FSIM

FSIM: A feature similarity index for image quality assessment. Image quality assessment (IQA) aims to use computational models to measure the image quality consistently with subjective evaluations. The well-known structural similarity index brings IQA from pixel- to structure-based stage. In this paper, a novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features. Specifically, the phase congruency (PC), which is a dimensionless measure of the significance of a local structure, is used as the primary feature in FSIM. Considering that PC is contrast invariant while the contrast information does affect HVS’ perception of image quality, the image gradient magnitude (GM) is employed as the secondary feature in FSIM. PC and GM play complementary roles in characterizing the image local quality. After obtaining the local quality map, we use PC again as a weighting function to derive a single quality score. Extensive experiments performed on six benchmark IQA databases demonstrate that FSIM can achieve much higher consistency with the subjective evaluations than state-of-the-art IQA metrics


References in zbMATH (referenced in 38 articles )

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  1. Lin, Jie; Huang, Ting-Zhu; Zhao, Xi-Le; Ma, Tian-Hui; Jiang, Tai-Xiang; Zheng, Yu-Bang: A novel non-convex low-rank tensor approximation model for hyperspectral image restoration (2021)
  2. Liu, Xinwu: Nonconvex total generalized variation model for image inpainting (2021)
  3. Upadhyaya, Vivek; Salim, Mohammad: Compressive sensing-based computed tomography imaging: an effective approach for COVID-19 detection (2021)
  4. Xu, Chen; Liu, Xiaoxia; Zheng, Jian; Shen, Lixin; Jiang, Qingtang; Lu, Jian: Nonlocal low-rank regularized two-phase approach for mixed noise removal (2021)
  5. Guo, Yumeng; Zeng, Li; Wang, Jiaxi; Shen, Zhaoqiang: Image reconstruction method for exterior circular cone-beam CT based on weighted directional total variation in cylindrical coordinates (2020)
  6. Jiang, Wei-wei; Zhong, Xin-xin; Zhou, Guang-quan; Guan, Qiu; Zheng, Yong-ping; Chen, Sheng-yong: An automatic measurement method of spinal curvature on ultrasound coronal images in adolescent idiopathic scoliosis (2020)
  7. Jin, Lianghai; Song, Enmin; Zhang, Wenhua: Denoising color images based on local orientation estimation and CNN classifier (2020)
  8. Likassa, Habte Tadesse; Xian, Wen; Tang, Xuan: New robust regularized shrinkage regression for high-dimensional image recovery and alignment via affine transformation and Tikhonov regularization (2020)
  9. Li, Yunyi; Liu, Li; Zhao, Yu; Cheng, Xiefeng; Gui, Guan: Nonconvex nonsmooth low-rank minimization for generalized image compressed sensing via group sparse representation (2020)
  10. Sadou, Besma; Lahoulou, Atidel; Bouden, Toufik: PFF-RVM: a new no reference image quality measure (2020)
  11. Tian, Chunwei; Fei, Lunke; Zheng, Wenxian; Xu, Yong; Zuo, Wangmeng; Lin, Chia-Wen: Deep learning on image denoising: an overview (2020)
  12. Wang, Yugang; Huang, Ting-Zhu; Zhao, Xi-Le; Jiang, Tai-Xiang: Video deraining via nonlocal low-rank regularization (2020)
  13. Zheng, Yu-Bang; Huang, Ting-Zhu; Zhao, Xi-Le; Jiang, Tai-Xiang; Ji, Teng-Yu; Ma, Tian-Hui: Tensor (N)-tubal rank and its convex relaxation for low-rank tensor recovery (2020)
  14. Huang, Jianping; Wang, Lihui; Zhu, Yuemin: Compressed sensing MRI reconstruction with multiple sparsity constraints on radial sampling (2019)
  15. Xue, Jize; Zhao, Yongqiang; Liao, Wenzhi; Chan, Jonathan Cheung-Wai: Hyper-Laplacian regularized nonlocal low-rank matrix recovery for hyperspectral image compressive sensing reconstruction (2019)
  16. Zhou, Wujie: Blind stereo image quality evaluation based on convolutional network and saliency weighting (2019)
  17. Zhou, Yu; Guo, Hainan: Collaborative block compressed sensing reconstruction with dual-domain sparse representation (2019)
  18. Chen, Yong; Huang, Ting-Zhu; Zhao, Xi-Le; Deng, Liang-Jian: Hyperspectral image restoration using framelet-regularized low-rank nonnegative matrix factorization (2018)
  19. Geng, Tianyu; Sun, Guiling; Xu, Yi; He, Jingfei: Truncated nuclear norm minimization based group sparse representation for image restoration (2018)
  20. Li, Bin; Shen, Chenyang; Chi, Yujie; Yang, Ming; Lou, Yifei; Zhou, Linghong; Jia, Xun: Multienergy cone-beam computed tomography reconstruction with a spatial spectral nonlocal means algorithm (2018)

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