一种用于提高点源法MTF检测精度的去噪方法 
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Denoising Method for Improving Detection Accuracy of Point Source Method by MTF
1 中国科学院上海技术物理研究所中国科学院智能红外感知重点实验室, 上海 200083
2 中国科学院大学, 北京 100049
图 & 表
图 1. 点源法原理示意图
Fig. 1. Schematic of point source method
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图 2. 理想的二维高斯分布。(a)三维视图;(b)剖面图
Fig. 2. Ideal two-dimensional Gaussian distribution. (a) Three-dimensional view; (b) sectional view
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图 3. 分区参数P对分区的影响
Fig. 3. Influence of partition parameter P on partition
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图 4. 分区参数P对MTF的MSE的影响(a=0.8)。(a)噪声标准差为30的图像在各种去噪方法下的MSE;(b)不同噪声标准差下参数P与MSE的关系曲线
Fig. 4. Influence of partition parameter P on MSE of MTF (a=0.8). (a) MSE of image with noise standard deviation of 30 under various denoising methods; (b) relationship between parameter P and MSE under different noise standard deviations
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图 5. 分区参数a对数据平滑的影响
Fig. 5. Influence of partition parameter a on data smoothing
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图 6. 平滑参数a对MTF的MSE的影响(P=0.3)。(a)噪声标准差为30的图像在各种去噪方法下的MSE;(b)不同噪声标准差下参数a与MSE的关系曲线
Fig. 6. Influence of smoothing parameter a on MSE of MTF (P=0.3). (a) MSE of image with noise standard deviation of 30 under various denoising methods; (b) relationship between parameter a and MSE under different noise standard deviations
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图 7. 离焦图像的序列。(a) image 1;(b) image 2;(c) image 3;(d) image 4;(e) image 5;(f) image 6
Fig. 7. Sequence of out-of-focus images. (a) image 1; (b) image 2; (c) image 3; (d) image 4; (e) image 5; (f) image 6
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图 8. 不同去噪方法的三维图和二维剖面图(噪声标准差为20)。(a)原始点源图;(b)加噪点源图;(c)均值滤波;(d)中值滤波;(e)小波滤波;(f)所提方法
Fig. 8. Three-dimensional images and two-dimensional profiles of different denoising methods (noise standard deviation is 20). (a) Original point source image; (b) add noise point source image; (c) mean filtering; (d) median filtering; (e) wavelet filtering; (f) proposed method
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图 9. 不同去噪方法处理后测得的MTF
Fig. 9. MTF measured after different denoising methods
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图 10. 不同去噪方法下MTF的MSE
Fig. 10. MSE of MTF under different denoising methods
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图 11. 不同去噪方法下图像的PSNR
Fig. 11. PSNR of images under different denoising methods
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图 12. 不同去噪方法下图像的SSIM
Fig. 12. SSIM of images under different denoising methods
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图 13. 采集的离焦点源图像序列。(a) -2.5 mm;(b) -2.0 mm;(c) -1.5 mm;(d) -1.0 mm;(e) 0 mm;(f) 1.0 mm;(g) +1.5 mm;(h) +2.0 mm;(i) +2.5 mm
Fig. 13. Sequences of captured out-of-focus source images. (a) -2.5 mm; (b) -2.0 mm; (c) -1.5 mm; (d) -1.0 mm; (e) 0 mm; (f) 1.0 mm; (g) +1.5 mm; (h) +2.0 mm; (i) +2.5 mm
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图 14. 不同去噪方法处理后测得的MTF(离焦量:-2.5 mm)
Fig. 14. MTF measured after different denoising methods (defocused amount: -2.5 mm)
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表 1所提去噪方法与传统滤波方法的性能对比
Table1. Performance comparison between proposed denoising method and traditional filtering methods
| Standard deviationof noise | Performance | Noiseimage | Proposedmethod | Mean filteringmethod | Medium filteringmethod | Wavelet filteringmethod |
|---|
| MSE | 0.0107 | 0.0023 | 0.0054 | 0.0060 | 0.0047 | | 5 | PSNR | 39.5126 | 41.5314 | 41.0826 | 40.9626 | 41.1824 | | SSIM | 0.9502 | 0.9940 | 0.9829 | 0.9789 | 0.9850 | | MSE | 0.0205 | 0.0019 | 0.0110 | 0.0133 | 0.0087 | | 10 | PSNR | 32.6774 | 35.9853 | 35.1366 | 35.2308 | 35.4256 | | SSIM | 0.7662 | 0.9814 | 0.9367 | 0.9236 | 0.9571 | | MSE | 0.0270 | 0.0040 | 0.0155 | 0.0173 | 0.0127 | | 15 | PSNR | 28.2794 | 32.4906 | 31.6207 | 32.0162 | 31.9966 | | SSIM | 0.5133 | 0.9616 | 0.8688 | 0.8452 | 0.9209 | | MSE | 0.0321 | 0.0061 | 0.0193 | 0.0203 | 0.0159 | | 20 | PSNR | 25.1575 | 30.0172 | 29.1058 | 29.9099 | 29.5053 | | SSIM | 0.3225 | 0.9391 | 0.7883 | 0.7601 | 0.8740 | | MSE | 0.0330 | 0.0096 | 0.0210 | 0.0223 | 0.0186 | | 25 | PSNR | 22.8968 | 28.0722 | 27.1704 | 28.4650 | 27.5833 | | SSIM | 0.2119 | 0.9148 | 0.7068 | 0.6848 | 0.8236 | | MSE | 0.0338 | 0.0098 | 0.0230 | 0.0242 | 0.0200 | | 30 | PSNR | 21.1746 | 26.4851 | 25.5809 | 27.3332 | 25.9853 | | SSIM | 0.1484 | 0.8875 | 0.6280 | 0.6173 | 0.7682 | | MSE | 0.0262 | 0.0056 | 0.0159 | 0.0172 | 0.0134 | | Mean value | PSNR | 28.2831 | 32.4303 | 31.6162 | 32.3196 | 31.9464 | | SSIM | 0.4854 | 0.9464 | 0.8186 | 0.8016 | 0.8881 |
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表 2实验器件参数
Table2. Parameters of experimental devices
| Experimentaldevice | Parameter | Value |
|---|
| Light source | Centerwavelength /nm | 550 | | CMOS detector | Cell size /mm | 0.00345 | | Lens | Focal length /mm | 50 | | Posteriorintercept/mm | 12.4 |
|
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表 3所提去噪方法与传统滤波方法的对比
Table3. Comparison between proposed denoising method and traditional filtering methods
| Parameter | Noise image | Mean filteringmethod | Mediumfiltering method | Wavelet filteringmethod | Proposedmethod |
|---|
| MTF curve area | 0.0563 | 0.0547 | 0.0706 | 0.0572 | 0.1403 | | PSNR | Inf | 36.2199 | 36.4075 | 36.8810 | 32.1785 | | SSIM | 1 | 0.8415 | 0.8337 | 0.8318 | 0.8283 |
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陈丽煊, 饶鹏, 朱含露, 孙莹莹, 贾良杰. 一种用于提高点源法MTF检测精度的去噪方法[J]. 激光与光电子学进展, 2020, 57(18): 181001. Lixuan Chen, Peng Rao, Hanlu Zhu, Yingying Sun, Liangjie Jia. Denoising Method for Improving Detection Accuracy of Point Source Method by MTF[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181001.
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