3 Speckle Noise Reduction and Enhancement for OCT Images
47
Table 3.3 Summary of different processing on OCT images and their related models based on
Fig. 3.2 [16]
Method
Application Modeling approach Researchers
Low-pass filtering
Denoising
S-II
Hee [93]
2D linear smoothing
Denoising
S-II
Huang [1]
Median filter
Denoising
S-II
Koozekanani [95], Rogowska
[96], Shahidi [97], Boyer [98],
Srinivasan [99], Lee et al. [100],
George[115], Herzog [116]
Adaptive wiener filter
Denoising
S-I
Ozcan [71]
Mean filter
Denoising
S-II
Ozcan [71], Ishikawa [101],
Mayer [102]
Two 1D filters
Denoising
S-II
Baroni [103]
Non-linear anisotropic
filter
Denoising
S-IV-2
Garvin[27], Cabrera Fernández
[34], Gregori [35],
Puvanathasan [62]
Complex diffusion
Denoising
S-IV-2
Bernardes [38], Salinas [26]
Directional filtering
Denoising
S-II
Bagci [37], Rogowska [36]
Adaptive vector-valued
kernel function
Denoising
T-TD
Mishra [40]
SVM approach
Denoising
S-II
Fuller [39]
Bayesian estimations
Denoising
S-I
Wong [105]
Sparsity-based denoising Denoising
T-TD3
Fang [54]
Sparsity-based denoising Denoising
T-TD3/TNX11
Fang [106]
Robust principal
component analysis
Denoising
T-TNX
Luan [41]
Complex wavelet/ksvd
Denoising
T-TD3/TNX12
Kafieh [22]
Wavelet –based methods Denoising
T-TNX11
Gupta [42], Mayer [43],
Pizurica [51], Adler [63],
Zlokolica [64], Quellec [107]
Dual tree complex
wavelet transformation
Denoising
T-TNX12
Mayer [43], Chitchian [45],
Kajic [46, 47], Rabbani [69],
Forouzanfar [108]
Curvelet transform
Denoising
T-TNX42
Jian [67], Jian [44]
Circular symmetric
Laplacian mixture model
in wavelet diffusion
Denoising
T-TNX11/T-I-1
Kafieh, R. [48]