Opto-Electronic Engineering, Volume. 51, Issue 12, 240222-1(2024)
Two-way guided updating network for light field image super-resolution
Figures & Tables(10)
Fig. 1. An overview of our diagram. (a) Overall network architecture diagram; (b) SE module; (c) TGU module; (d) SAF module; (e) MLPR module
Fig. 2. Comparison between SFRD and FRD. (a) SRFD module; (b) RFD module
Fig. 3. Visual results of the “Origima” and “Bicycle” scene with 2×SR
Fig. 4. Visual results of the “Bedroom” and “LEGO Knights” scene with 4×SR
Fig. 5. A visualization of PSNR distribution among different perspectives on 5×5 LFs for 2×SR
Fig. 6. Variations of each module. (a) RSPC w/o parallel convolution; (b) RSPC w/o series convolution; (c) RSPC w/o residual; (d) Half TGU
Fig. 7. Optimal selection of the number of TGUs. (a) PSNR and the number of parameters values increase with the number of TGUs; (b) SSIM and FLOPs values increase with the number of TGUs
Table 1. PSNR/SSIM values by different methods for 2×SR and 4×SR
View tableView in ArticleTable 1. PSNR/SSIM values by different methods for 2×SR and 4×SR
Method Scale Dataset Average EPFL HCInew HCIold INRIA STFgantry bicubic 2× 29.74/0.9376 31.89/0.9356 37.69/0.9785 31.33/0.9577 31.06/0.9498 32.34/0.9518 EDSR[ 32 ]2× 33.09/0.9631 34.83/0.9594 41.01/0.9875 34.97/0.9765 36.29/0.9819 36.04/0.9728 RCAN[ 33 ]2× 33.16/0.9635 34.98/0.9602 41.05/0.9875 35.01/0.9769 36.33/0.9825 36.11/0.9741 ResLF[ 15 ]2× 32.75/0.9672 36.07/0.9715 42.61/0.9922 34.57/0.9784 36.89/0.9873 36.58/0.9793 LFSSR[ 12 ]2× 33.69/0.9748 36.86/0.9753 43.75/0.9939 35.27/0.9834 38.07/0.9902 37.53/0.9835 LF-Internet[ 21 ]2× 34.14/0.9761 37.28/0.9769 44.45/ 0.9945 35.80/0.9846 38.72/0.9916 38.08/0.9847 LF-DFnet[ 20 ]2× 34.44/0.9766 37.44/0.9786 44.23/0.9943 36.36/0.9841 39.61/0.9935 38.42/0.9854 LF-IInet[ 22 ]2× 34.68 37.74/0.9789 44.84 /0.9948 36.57 /0.985339.86/0.9935 38.74 /0.9859 DPT[ 20 ]2× 34.48/0.9759 37.35/0.9770 44.31/0.9943 36.40/0.9843 39.52/0.9928 38.41/0.9849 LF-ADEnet[ 17 ]2× 34.58/0.9772 37.92 /0.9796 44.84 /0.9948 36.59 0.9854 40.11 /0.9939 38.81 /0.9862 LF-MDFnet[ 18 ]2× 34.62/ 0.9844 37.37/0.9772 44.06/0.9823 36.23/0.9791 39.42/0.9923 38.34/0.9831 LF-TGUnet 2× 34.67 0.9776 37.80 0.9791 44.78 0.9948 36.46 /0.9857 39.95 0.9936 38.73 /0.9862 bicubic 4× 25.14/0.8324 27.61/0.8517 32.42/0.9344 26.82/0.8867 25.93/0.8452 27.58/0.8661 EDSR[ 32 ]4× 27.84/0.8858 29.60/0.8874 35.18/0.9538 29.66/0.9259 28.70/0.9075 30.20/0.9121 RCAN[ 33 ]4× 27.88/0.8863 29.63/0.8880 35.20/0.9540 29.76/0.9273 28.90/0.9110 30.27/0.9133 ResLF[ 15 ]4× 27.46/0.8899 29.92/0.9011 36.12/0.9651 29.64/0.9339 28.99/0.9214 30.43/0.9223 LFSSR[ 12 ]4× 28.27/0.9080 30.72/0.9124 36.70/0.9690 30.31/0.9446 30.15/0.9385 31.23/0.9345 LF-Internet[ 21 ]4× 28.67/0.9143 30.98/0.9165 37.11/0.9715 30.64/0.9486 30.53/0.9426 31.59/0.9387 LF-DFnet[ 13 ]4× 28.77/0.9165 31.23/0.9196 37.32/0.9718 30.83/0.9503 31.15/0.9494 31.86/0.9415 LF-IInet[ 22 ]4× 29.11 /0.9194 31.36 /0.9211 37.62 /0.9737 31.08 /0.951631.21 /0.9495 32.08 /0.9431 DPT[ 20 ]4× 28.93/0.9167 31.19/0.9186 37.39/0.9720 30.96/0.9502 31.14/0.9487 31.92/0.9412 LF-ADEnet[ 17 ]4× 28.81/ 0.9190 31.30/0.9206 37.39/0.9725 30.81/0.9513 31.15/0.9494 31.86/0.9429 LF-MDFnet[ 18 ]4× 28.70/0.9049 31.41/0.9146 37.42/ 0.9856 30.86/ 0.9521 30.86/0.9365 31.85/0.9387 LF-TGUnet 4× 28.96 0.9189 31.42 0.9215 37.63 0.9734 31.28 0.9529 31.36 0.9511 32.13 0.9436
Table 2. Comparisons of the number of parameters (#Params), FLOPs, and running time
View tableView in ArticleTable 2. Comparisons of the number of parameters (#Params), FLOPs, and running time
Method EDSR[ 32 ]RCAN[ 33 ]ResLF[ 15 ]LFSSR[ 12 ]LF-Internet[ 21 ]LF-DFnet[ 13 ]LF-IInet[ 22 ]DPT[ 20 ]LF-ADEnet[ 17 ]LF-MDFnet[ 18 ]LF-TGUnet #Params/M 2× 38.62 15.31 6.35 0.81 4.80 3.94 4.84 3.73 12.74 5.37 4.37 4× 38.89 15.36 6.79 1.61 5.23 3.99 4.89 3.78 12.80 5.42 4.42 FLOPs/G 2× 39.56×25 15.59×25 37.06 25.70 47.46 57.22 56.16 57.44 238.92 135.65 78.84 4× 40.66×25 15.65×25 39.70 128.44 50.10 57.31 57.42 58.64 240.51 136.91 80.11 Running time /s 2× 0.44 13.10 2.95 0.21 1.45 1.73 0.55 7.56 4.85 3.53 3.02 4× 0.29 3.54 0.95 0.16 0.47 0.55 0.21 2.06 1.75 1.77 0.81
Table 3. Validity verification of each module
View tableView in ArticleTable 3. Validity verification of each module
Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Case 7 (LF-TGUnet) Spatial and angular information decoupling RPSC w/o parallel convolution √ RPSC w/o series convolution √ RPSC w/o residual √ RSPC √ √ √ √ Spatial and angular features guided updating half TGU √ TGU √ √ √ √ √ √ TGU w/o MLPR √ MLPR √ √ √ √ √ √ Data reconstruction RFD √ SRFD √ √ √ √ √ √ #Params/M 4.30 4.34 4.42 4.46 4.41 5.70 4.42 Dataset EPFL 28.83/0.9184 29.01 /0.9196 25.26/0.8324 27.82/0.8856 28.87/ 0.9195 29.18 28.96 /0.9189 HCInew 31.40 /0.921431.40 /0.9216 27.71/0.8517 29.64/0.8869 31.37/0.9212 31.23/0.9193 31.42 0.9215 HCIold 37.55/0.9730 37.57 /0.973132.58/0.9344 35.12/0.9536 37.51/ 0.9732 37.30/0.9720 37.63 0.9734 INRIA 30.89/0.9512 30.97/0.9516 26.95/0.8867 29.79/0.9264 31.02/ 0.9520 31.08 /0.950531.28 0.9529 STFgantry 31.35 /0.951031.35 /0.9511 26.09/0.8452 28.78/0.9091 31.29/ 0.9512 31.07/0.9486 31.36 0.9511 Average (PSNR/SSIM) 32.00/0.9430 32.06 /0.9434 27.72/0.8701 30.23/0.9123 32.01/ 0.9434 31.97/0.9416 32.13 0.9436 Deviation −0.13/−0.0006 −0.07/−0.0002 −4.41/−0.0735 −1.90/−0.0313 −0.12/−0.0002 −0.16/−0.0020 0 /0
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Li Huang, Tianqi Lv, Yingchun Wu, Jiani Chen. Two-way guided updating network for light field image super-resolution[J]. Opto-Electronic Engineering, 2024, 51(12): 240222-1
Paper Information
Category: Article
Received: Sep. 18, 2024
Accepted: Dec. 3, 2024
Published Online: Feb. 21, 2025
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