Research on Digital Drive Imaging Quality of Silicon-based OLED Micro Display Based on Super Pixel

Yuan JI; Honggang CHEN; Baoliang CHEN; Yin ZHANG; Yiqing XU

doi:10.3788/gzxb20235209.0911002

Journals >Acta Photonica Sinica >Volume 52 >Issue 9 >Page 0911002 > Article

Acta Photonica Sinica
Vol. 52, Issue 9, 0911002 (2023)

Research on Digital Drive Imaging Quality of Silicon-based OLED Micro Display Based on Super Pixel

Yuan JI^1,2, Honggang CHEN^1,*, Baoliang CHEN¹, Yin ZHANG², and Yiqing XU¹

Author Affiliations

¹Microelectronics Research and Development Center，Shanghai University，Shanghai 200072，China

²School of Mechatronic Engineering and Automation，Shanghai University，Shanghai 200072，China

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DOI: 10.3788/gzxb20235209.0911002 Cite this Article

Yuan JI, Honggang CHEN, Baoliang CHEN, Yin ZHANG, Yiqing XU. Research on Digital Drive Imaging Quality of Silicon-based OLED Micro Display Based on Super Pixel[J]. Acta Photonica Sinica, 2023, 52(9): 0911002 Copy Citation Text

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Fig. 1. Formation of super pixel

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Fig. 2. Drive circuit of super pixel

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Fig. 3. Super pixel processing flow of image

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Fig. 4. Model of super pixel

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Fig. 5. Formation principle of DFC

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Fig. 6. The integration process of human eye to subframe subfield

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Fig. 7. Block diagram of controller system

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Fig. 8. Block diagram of super pixel processing module

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Fig. 9. Test platform of hardware

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Fig. 10. Simulation image of super pixel model

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Fig. 11. DFC under different scanning modes

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Image	Even frame		Odd frame		Super pixel frame
Image	PSNR	SSIM	PSNR	SSIM	PSNR	SSIM
1	31.980	0.925	32.490	0.924	36.589	0.961
2	31.615	0.898	31.945	0.897	36.204	0.949
3	27.172	0.829	27.536	0.828	31.069	0.908
4	30.458	0.913	30.680	0.914	35.487	0.957
5	30.673	0.908	30.781	0.908	35.104	0.957
6	31.044	0.903	31.645	0.902	35.773	0.949
7	28.068	0.843	28.329	0.844	32.387	0.925
8	30.677	0.909	29.847	0.905	34.406	0.949
9	30.383	0.864	30.746	0.866	34.253	0.927
10	27.784	0.847	26.714	0.847	31.317	0.923
11	27.984	0.861	26.918	0.857	32.087	0.924
12	28.669	0.918	28.596	0.918	33.533	0.956
13	27.916	0.876	27.709	0.876	31.867	0.936
14	29.850	0.866	29.933	0.864	33.833	0.932
15	32.067	0.946	33.518	0.945	37.381	0.975
Average	29.756	0.887	29.826	0.886	34.086	0.942

Table 1. The PSNR and SSIM comparison of image processed by super pixel model

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Number	19-SubFrame		CGPWM^［7］		Super pixel
Number	JND $_{T_{m a x}}$ =0	JND $_{T_{m a x}}$ ≤8	JND $_{T_{m a x}}$ =0	JND $_{T_{m a x}}$ ≤8	JND $_{T_{m a x}}$ =0	JND $_{T_{m a x}}$ ≤8
1	87.970	94.136	90.261	95.640	90.885	98.978
2	89.040	90.785	89.310	91.132	93.797	99.791
3	91.252	94.859	91.654	95.178	93.960	99.926
4	89.688	93.309	90.049	93.638	93.476	99.684
5	91.921	94.587	93.122	95.563	94.574	98.578
6	88.981	93.950	89.847	94.674	92.628	99.370
7	90.703	94.492	91.429	95.052	93.889	99.749
8	89.847	94.043	91.517	95.397	91.621	97.446
9	87.965	93.131	88.377	93.460	91.454	99.715
10	87.992	93.223	88.550	93.652	90.928	99.622
11	89.866	93.988	90.605	94.633	93.204	99.287
12	89.328	93.759	89.680	94.061	92.113	99.855
13	89.919	94.206	91.088	95.956	91.859	98.009
14	89.882	93.900	90.408	94.404	93.008	99.405
15	93.368	95.294	93.850	95.633	96.982	99.608
16	90.553	94.205	90.798	94.507	94.386	99.838
17	90.839	93.895	91.401	94.336	95.033	99.726
18	91.851	94.024	93.023	94.940	95.799	98.734
19	89.769	93.975	90.590	94.665	92.466	99.058
20	94.794	96.713	95.071	97.040	96.608	99.686
21	89.037	94.004	90.026	94.727	92.382	99.304
22	88.305	93.313	89.093	94.000	91.308	99.299
23	90.089	93.783	90.823	94.422	93.517	99.810
24	90.569	94.419	92.122	95.642	92.876	98.783
Average	90.147	94.000	90.946	94.681	93.281	99.302

Table 2. JND integration results of different scanning methods（%）

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