Abstract

We present an on-chip, widefield fluorescence microscope, which consists of a diffuser placed a few millimeters away from a traditional image sensor. The diffuser replaces the optics of a microscope, resulting in a compact and easy-to-assemble system with a practical working distance of over 1.5 mm. Furthermore, the diffuser encodes volumetric information, enabling refocusability in post-processing and three-dimensional (3D) imaging of sparse samples from a single acquisition. Reconstruction of images from the raw data requires a precise model of the system, so we introduce a practical calibration scheme and a physics-based forward model to efficiently account for the spatially-varying point spread function (PSF). To improve performance in low-light, we propose a random microlens diffuser, which consists of many small lenslets randomly placed on the mask surface and yields PSFs that are robust to noise. We build an experimental prototype and demonstrate our system on both planar and 3D samples.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2018 (4)

2017 (5)

P. Berto, H. Rigneault, and M. Guillon, “Wavefront sensing with a thin diffuser,” Opt. Lett. 42(24), 5117–5120 (2017).
[Crossref]

G. Kim, K. Isaacson, R. Palmer, and R. Menon, “Lensless photography with only an image sensor,” Appl. Opt. 56(23), 6450–6456 (2017).
[Crossref]

T. Kamal, R. Watkins, Z. Cen, J. Rubinstein, G. Kong, and W. M. Lee, “Design and fabrication of a passive droplet dispenser for portable high resolution imaging system,” Sci. Rep. 7(1), 41482 (2017).
[Crossref]

J. K. Adams, V. Boominathan, B. W. Avants, D. G. Vercosa, F. Ye, R. G. Baraniuk, J. T. Robinson, and A. Veeraraghavan, “Single-frame 3D fluorescence microscopy with ultraminiature lensless FlatScope,” Sci. Adv. 3(12), e1701548 (2017).
[Crossref]

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[Crossref]

2016 (1)

2014 (1)

D. G. Stork and P. R. Gill, “Optical, mathematical, and computational foundations of lensless ultra-miniature diffractive imagers and sensors,” Int. J. on Adv. Syst. Meas. 7, 4 (2014).

2013 (1)

2012 (2)

A. Greenbaum, W. Luo, T. Su, Z. Göröcs, L. Xue, S. O. Isikman, A. F. Coskun, O. Mudanyali, and A. Ozcan, “Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy,” Nat. Methods 9(9), 889–895 (2012).
[Crossref]

K. Kagawa, K. Yamada, E. Tanaka, and J. Tanida, “A three-dimensional multifunctional compound-eye endoscopic system with extended depth of field,” Electron. Comm. Jpn. 95(11), 14–27 (2012).
[Crossref]

2011 (2)

G. Zheng, S. A. Lee, Y. Antebi, M. B. Elowitz, and C. Yang, “The ePetri dish, an on-chip cell imaging platform based on subpixel perspective sweeping microscopy (SPSM),” Proc. Natl. Acad. Sci. 108(41), 16889–16894 (2011).
[Crossref]

A. F. Coskun, I. Sencan, T. Su, and A. Ozcan, “Lensfree fluorescent on-chip imaging of transgenic caenorhabditis elegans over an ultra-wide field-of-view,” PLoS One 6(1), e15955 (2011).
[Crossref]

2010 (3)

A. F. Coskun, I. Sencan, T. Su, and A. Ozcan, “Lensless wide-field fluorescent imaging on a chip using compressive decoding of sparse objects,” Opt. Express 18(10), 10510–10523 (2010).
[Crossref]

O. Mudanyali, D. Tseng, C. Oh, S. O. Isikman, I. Sencan, W. Bishara, C. Oztoprak, S. Seo, B. Khademhosseini, and A. Ozcan, “Compact, light-weight and cost-effective microscope based on lensless incoherent holography for telemedicine applications,” Lab Chip 10(11), 1417–1428 (2010).
[Crossref]

W. Bishara, T. Su, A. F. Coskun, and A. Ozcan, “Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution,” Opt. Express 18(11), 11181–11191 (2010).
[Crossref]

2009 (1)

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imaging Sci. 2(1), 183–202 (2009).
[Crossref]

2008 (3)

E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).
[Crossref]

E. J. Candès, “The restricted isometry property and its implications for compressed sensing,” CR Math. 346(9-10), 589–592 (2008).
[Crossref]

X. Cui, L. M. Lee, X. Heng, W. Zhong, P. W. Sternberg, D. Psaltis, and C. Yang, “Lensless high-resolution on-chip optofluidic microscopes for caenorhabditis elegans and cell imaging,” Proc. Natl. Acad. Sci. 105(31), 10670–10675 (2008).
[Crossref]

2007 (1)

R. Horisaki, S. Irie, Y. Ogura, and J. Tanida, “Three-dimensional information acquisition using a compound imaging system,” Opt. Rev. 14(5), 347–350 (2007).
[Crossref]

2006 (1)

D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52(4), 1289–1306 (2006).
[Crossref]

2005 (1)

R. Ng, M. Levoy, M. Brédif, G. Duval, M. Horowitz, and P. Hanrahan, “Light field photography with a hand-held plenoptic camera,” Comput. Sci. Tech. Rep. CSTR 2, 1–11 (2005).

2001 (1)

1994 (1)

D. MacFarlane, V. Narayan, J. Tatum, W. Cox, T. Chen, and D. Hayes, “Microjet fabrication of microlens arrays,” IEEE Photonics Technol. Lett. 6(9), 1112–1114 (1994).
[Crossref]

1992 (1)

E. H. Adelson and J. Y. A. Wang, “Single lens stereo with a plenoptic camera,” IEEE Trans. Pattern Anal. Machine Intell. 14(2), 99–106 (1992).
[Crossref]

1989 (1)

1930 (1)

1908 (1)

G. Lippmann, “Epreuves reversibles donnant la sensation du relief,” J. Phys. Theor. Appl. 7(1), 821–825 (1908).
[Crossref]

Adams, J. K.

J. K. Adams, V. Boominathan, B. W. Avants, D. G. Vercosa, F. Ye, R. G. Baraniuk, J. T. Robinson, and A. Veeraraghavan, “Single-frame 3D fluorescence microscopy with ultraminiature lensless FlatScope,” Sci. Adv. 3(12), e1701548 (2017).
[Crossref]

Adelson, E. H.

E. H. Adelson and J. Y. A. Wang, “Single lens stereo with a plenoptic camera,” IEEE Trans. Pattern Anal. Machine Intell. 14(2), 99–106 (1992).
[Crossref]

Alguri, K. S.

A. B. Zoubi, K. S. Alguri, G. Kim, V. J. Mathews, R. Menon, and J. B. Harley, “Fast imaging in cannula microscope using orthogonal matching pursuit,” in 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE), (IEEE, 2015), pp. 214–219.

Andalman, A.

Antebi, Y.

G. Zheng, S. A. Lee, Y. Antebi, M. B. Elowitz, and C. Yang, “The ePetri dish, an on-chip cell imaging platform based on subpixel perspective sweeping microscopy (SPSM),” Proc. Natl. Acad. Sci. 108(41), 16889–16894 (2011).
[Crossref]

Antipa, N.

N. Antipa, G. Kuo, R. Heckel, B. Mildenhall, E. Bostan, R. Ng, and L. Waller, “DiffuserCam: lensless single-exposure 3D imaging,” Optica 5(1), 1–9 (2018).
[Crossref]

G. Kuo, N. Antipa, R. Ng, and L. Waller, “DiffuserCam: Diffuser-based lensless cameras,” in Computational Optical Sensing and Imaging, (Optical Society of America, 2017), pp. CTu3B–2.

N. Antipa, P. Oare, E. Bostan, R. Ng, and L. Waller, “Video from stills: Lensless imaging with rolling shutter,” in 2019 IEEE International Conference on Computational Photography (ICCP), (IEEE, 2019), pp. 1–8.

F. L. Liu, V. Madhavan, N. Antipa, G. Kuo, S. Kato, and L. Waller, “Single-shot 3D fluorescence microscopy with Fourier DiffuserCam,” in Novel Techniques in Microscopy, (Optical Society of America, 2019), pp. NS2B–3.

K. Yanny, N. Antipa, R. Ng, and L. Waller, “Miniature 3D fluorescence microscope using random microlenses,” in Optics and the Brain, (Optical Society of America, 2019), pp. BT3A–4.

N. Antipa, S. Necula, R. Ng, and L. Waller, “Single-shot diffuser-encoded light field imaging,” in 2016 IEEE International Conference on Computational Photography (ICCP), (2016), pp. 1, 11.

Anwar, M.

Asif, M. S.

M. S. Asif, A. Ayremlou, A. Veeraraghavan, R. Baraniuk, and A. Sankaranarayanan, “FlatCam: Replacing lenses with masks and computation,” in Computer Vision Workshop (ICCVW), 2015 IEEE International Conference on, (IEEE, 2015), pp. 663–666.

Avants, B. W.

J. K. Adams, V. Boominathan, B. W. Avants, D. G. Vercosa, F. Ye, R. G. Baraniuk, J. T. Robinson, and A. Veeraraghavan, “Single-frame 3D fluorescence microscopy with ultraminiature lensless FlatScope,” Sci. Adv. 3(12), e1701548 (2017).
[Crossref]

Ayremlou, A.

M. S. Asif, A. Ayremlou, A. Veeraraghavan, R. Baraniuk, and A. Sankaranarayanan, “FlatCam: Replacing lenses with masks and computation,” in Computer Vision Workshop (ICCVW), 2015 IEEE International Conference on, (IEEE, 2015), pp. 663–666.

Baraniuk, R.

M. S. Asif, A. Ayremlou, A. Veeraraghavan, R. Baraniuk, and A. Sankaranarayanan, “FlatCam: Replacing lenses with masks and computation,” in Computer Vision Workshop (ICCVW), 2015 IEEE International Conference on, (IEEE, 2015), pp. 663–666.

Baraniuk, R. G.

J. K. Adams, V. Boominathan, B. W. Avants, D. G. Vercosa, F. Ye, R. G. Baraniuk, J. T. Robinson, and A. Veeraraghavan, “Single-frame 3D fluorescence microscopy with ultraminiature lensless FlatScope,” Sci. Adv. 3(12), e1701548 (2017).
[Crossref]

Beck, A.

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imaging Sci. 2(1), 183–202 (2009).
[Crossref]

Berto, P.

Bishara, W.

W. Bishara, T. Su, A. F. Coskun, and A. Ozcan, “Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution,” Opt. Express 18(11), 11181–11191 (2010).
[Crossref]

O. Mudanyali, D. Tseng, C. Oh, S. O. Isikman, I. Sencan, W. Bishara, C. Oztoprak, S. Seo, B. Khademhosseini, and A. Ozcan, “Compact, light-weight and cost-effective microscope based on lensless incoherent holography for telemedicine applications,” Lab Chip 10(11), 1417–1428 (2010).
[Crossref]

Boominathan, V.

J. K. Adams, V. Boominathan, B. W. Avants, D. G. Vercosa, F. Ye, R. G. Baraniuk, J. T. Robinson, and A. Veeraraghavan, “Single-frame 3D fluorescence microscopy with ultraminiature lensless FlatScope,” Sci. Adv. 3(12), e1701548 (2017).
[Crossref]

Boser, B. E.

Bostan, E.

N. Antipa, G. Kuo, R. Heckel, B. Mildenhall, E. Bostan, R. Ng, and L. Waller, “DiffuserCam: lensless single-exposure 3D imaging,” Optica 5(1), 1–9 (2018).
[Crossref]

N. Antipa, P. Oare, E. Bostan, R. Ng, and L. Waller, “Video from stills: Lensless imaging with rolling shutter,” in 2019 IEEE International Conference on Computational Photography (ICCP), (IEEE, 2019), pp. 1–8.

Brédif, M.

R. Ng, M. Levoy, M. Brédif, G. Duval, M. Horowitz, and P. Hanrahan, “Light field photography with a hand-held plenoptic camera,” Comput. Sci. Tech. Rep. CSTR 2, 1–11 (2005).

Broxton, M.

Candès, E. J.

E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).
[Crossref]

E. J. Candès, “The restricted isometry property and its implications for compressed sensing,” CR Math. 346(9-10), 589–592 (2008).
[Crossref]

Cen, Z.

T. Kamal, R. Watkins, Z. Cen, J. Rubinstein, G. Kong, and W. M. Lee, “Design and fabrication of a passive droplet dispenser for portable high resolution imaging system,” Sci. Rep. 7(1), 41482 (2017).
[Crossref]

Chen, T.

D. MacFarlane, V. Narayan, J. Tatum, W. Cox, T. Chen, and D. Hayes, “Microjet fabrication of microlens arrays,” IEEE Photonics Technol. Lett. 6(9), 1112–1114 (1994).
[Crossref]

Cohen, N.

Coskun, A. F.

A. Greenbaum, W. Luo, T. Su, Z. Göröcs, L. Xue, S. O. Isikman, A. F. Coskun, O. Mudanyali, and A. Ozcan, “Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy,” Nat. Methods 9(9), 889–895 (2012).
[Crossref]

A. F. Coskun, I. Sencan, T. Su, and A. Ozcan, “Lensfree fluorescent on-chip imaging of transgenic caenorhabditis elegans over an ultra-wide field-of-view,” PLoS One 6(1), e15955 (2011).
[Crossref]

W. Bishara, T. Su, A. F. Coskun, and A. Ozcan, “Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution,” Opt. Express 18(11), 11181–11191 (2010).
[Crossref]

A. F. Coskun, I. Sencan, T. Su, and A. Ozcan, “Lensless wide-field fluorescent imaging on a chip using compressive decoding of sparse objects,” Opt. Express 18(10), 10510–10523 (2010).
[Crossref]

Cox, W.

D. MacFarlane, V. Narayan, J. Tatum, W. Cox, T. Chen, and D. Hayes, “Microjet fabrication of microlens arrays,” IEEE Photonics Technol. Lett. 6(9), 1112–1114 (1994).
[Crossref]

Cui, X.

X. Cui, L. M. Lee, X. Heng, W. Zhong, P. W. Sternberg, D. Psaltis, and C. Yang, “Lensless high-resolution on-chip optofluidic microscopes for caenorhabditis elegans and cell imaging,” Proc. Natl. Acad. Sci. 105(31), 10670–10675 (2008).
[Crossref]

Deisseroth, K.

Donoho, D. L.

D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52(4), 1289–1306 (2006).
[Crossref]

Duval, G.

R. Ng, M. Levoy, M. Brédif, G. Duval, M. Horowitz, and P. Hanrahan, “Light field photography with a hand-held plenoptic camera,” Comput. Sci. Tech. Rep. CSTR 2, 1–11 (2005).

Elowitz, M. B.

G. Zheng, S. A. Lee, Y. Antebi, M. B. Elowitz, and C. Yang, “The ePetri dish, an on-chip cell imaging platform based on subpixel perspective sweeping microscopy (SPSM),” Proc. Natl. Acad. Sci. 108(41), 16889–16894 (2011).
[Crossref]

Fergus, R.

R. Fergus, A. Torralba, and W. T. Freeman, “Random Lens Imaging,” Tech. rep., Massachusetts Institute of Technology (2006).

Freeman, W. T.

R. Fergus, A. Torralba, and W. T. Freeman, “Random Lens Imaging,” Tech. rep., Massachusetts Institute of Technology (2006).

Friedrich, R. W.

Gill, P. R.

D. G. Stork and P. R. Gill, “Optical, mathematical, and computational foundations of lensless ultra-miniature diffractive imagers and sensors,” Int. J. on Adv. Syst. Meas. 7, 4 (2014).

Göröcs, Z.

A. Greenbaum, W. Luo, T. Su, Z. Göröcs, L. Xue, S. O. Isikman, A. F. Coskun, O. Mudanyali, and A. Ozcan, “Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy,” Nat. Methods 9(9), 889–895 (2012).
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X. Cui, L. M. Lee, X. Heng, W. Zhong, P. W. Sternberg, D. Psaltis, and C. Yang, “Lensless high-resolution on-chip optofluidic microscopes for caenorhabditis elegans and cell imaging,” Proc. Natl. Acad. Sci. 105(31), 10670–10675 (2008).
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K. Yanny, N. Antipa, R. Ng, and L. Waller, “Miniature 3D fluorescence microscope using random microlenses,” in Optics and the Brain, (Optical Society of America, 2019), pp. BT3A–4.

N. Antipa, S. Necula, R. Ng, and L. Waller, “Single-shot diffuser-encoded light field imaging,” in 2016 IEEE International Conference on Computational Photography (ICCP), (2016), pp. 1, 11.

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N. Antipa, P. Oare, E. Bostan, R. Ng, and L. Waller, “Video from stills: Lensless imaging with rolling shutter,” in 2019 IEEE International Conference on Computational Photography (ICCP), (IEEE, 2019), pp. 1–8.

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Supplementary Material (1)

NameDescription
» Visualization 1       Video of 15 um fluorescent beads flowing through a microfluidic channel, captured by our on-chip diffuser microscope at 10 fps. The channel outlines are superimposed for visualization purposes.

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Figures (9)

Fig. 1.
Fig. 1. Our light-weight and portable on-chip microscope consists of a random microlens diffuser placed a few millimeters above an image sensor. Using only a sparse grid of calibration measurements, 3D images are reconstructed with a local convolution model that accounts for the spatially-varying point spread functions (PSFs).
Fig. 2.
Fig. 2. The two-part forward model, which consists of a diffuser component ($h_{\textrm {d}}$) and sensor component ($h_{\textrm {sensor}}$), informs interpolation between calibration measurements. Consider two calibration points located on-axis at $x_0$ and off-axis at $x_{1}$. Based on the two-part model, each PSF consists of a high frequency signal due to the diffuser ($h_{\textrm {d}}$) multiplied by the angular-dependent sensor response ($h_{\textrm {sensor}}$). In the off-axis PSF, $h_{\textrm {d}}$ is translated to the left while $h_{\textrm {sensor}}$ remains directly under the point source. To interpolate between the two calibration measurements, first we register the component due to the diffuser. Then we approximate the PSF at $x^{*}$ by taking a linear combination of the registered PSFs where the weights ($\alpha$) are based on the distance between the calibration location and $x^*$. We extend this to 2D using bilinear interpolation.
Fig. 3.
Fig. 3. The number of calibration measurements needed for our local convolution model is determined by the angular falloff of the sensor. (a) Experimentally measured angular falloff, $f(\theta )$, fit to a Gaussian curve with $\sigma = 13 ^\circ$. (b) Fourier transform after $f(\theta )$ is transformed based on Eq. (10), which is used to determine the maximum frequency, and thus the Nyquist sampling, in order to determine the necessary calibration sampling. (c) To test this, we simulate PSF measurements and (d) raw data using the Gaussian approximation of $f(\theta )$. (e) We then reconstruct the sample using the local convolution model with varying spacing between the calibration measurements. When calibration images satisfy the Nyquist sampling (0.4 mm apart), the model performs well, but when samples are spaced further apart, the reconstruction degrades.
Fig. 4.
Fig. 4. Simulation comparing PSFs for depth-resolved imaging. A microscope objective has good noise performance but fails to capture 3D information. A smooth diffuser’s PSF has significant background light causing noise amplification, as does the periodicity of the regular microlens array. Our random microlens diffuser has a non-periodic PSF with high contrast, resulting in good noise performance and 3D reconstructions. All simulations have the same quantity of Gaussian noise added to the raw data.
Fig. 5.
Fig. 5. Simulation comparing PSF robustness to shot noise at a single depth. A microscope objective has the best noise performance for 2D imaging, but it does not extend to depth-resolved imaging nor to miniaturized systems. Of the PSFs with 3D capabilities, the random microlens diffuser is most robust to shot noise.
Fig. 6.
Fig. 6. Experimental resolution characterization. (a) Resolution is measured by determining the minimum separation distance at which two fluorescent beads are resolvable. The experimental resolution can be predicted by calculating inner products of a PSF with shifts and scales of itself; points are considered resolvable when the inner product is below 0.8. The predicted resolution is calculated at 12 different lateral locations in the FoV. The range of values is depicted by the filled area in the plot, and the solid line is the mean. (b) USAF resolution target shows group 6, element 1 containing 7.8 µm bars (boxed) is clearly resolvable, which matches the two-point resolution.
Fig. 7.
Fig. 7. Experimental videos captured with our diffuser microscope at 10 fps. (a) Fluorescent beads flowing in a microfluidic channel. Channel outlines are superimposed for visualization purposes, and the full video is in Visualization 1. (b) NeuroD:GCaMP6f larval zebrafish, 6 days old. Change in fluorescence ($\Delta f$) compared to a 20th percentile baseline is shown in red and indicates neural activity.
Fig. 8.
Fig. 8. 3D reconstruction of 15 µm fluorescent beads, axially separated by coverslips. The focal stack from a traditional fluorescence microscope (5$\times$, 0.15 NA) is shown for comparison, with close-ups on the right. Our diffuser microscope reconstructs all depth planes from a single acquisition (bottom right) and removes out-of-focus light.
Fig. 9.
Fig. 9. 3D reconstruction of fixed brine shrimp tagged with eosin, shown at three different axial planes. The focal stack from a traditional fluorescence microscope (10$\times$, 0.45 NA) is shown for comparison. Our diffuser microscope reconstructs 3D from a single acquisition and recovers the thin antenna structures at the correct depths.

Equations (13)

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b ( x , y ) = C ( x , y , z ) h ( x , y ; x , y , z ) x ( x , y , z ) + g ( x , y ) .
h d ( x , y ; x , y , z ) = h d ( s x + s d z x , s y + s d z y ; z ) ,
s = z ( d + z ) z ( d + z ) .
h sensor ( x , y ; x , y , z ) = f ( tan 1 ( ( x x ) 2 + ( y y ) 2 d + z ) ) .
h ( x , y ; x , y , z ) = h d ( s x + s d z x , s y + s d z y ; z ) f ( tan 1 ( ( x x ) 2 + ( y y ) 2 d + z ) ) .
h sensor ( x , y ; x , y , z ) = f ( tan 1 ( x 2 + y 2 d + z ) ) ,
h ~ i ( x , y ; z ) = h i ( s i x s i Δ x i , s i y s i Δ y i ) = h d ( x , y ; z ) f ( tan 1 ( ( s i x d z x i x i ) 2 + ( s i y d z y i y i ) 2 d + z i ) )
s i = z ( d + z i ) z i ( d + z ) , Δ x i = d z s i x i , Δ y i = d z s i y i .
h ( x , y ; x , y , z ) i α i ( x , y , z ) h ~ i ( x + d z x , y + d z y ; z ) .
b ( x , y ) = C ( z , i ) ( x , y ) α i ( x , y , z ) x ( x , y , z ) h ~ i ( x + d z x , y + d z y ; z ) = C ( z , i ) [ α i ( z d x , z d y , z ) x ( z d x , z d y , z ) ] h ~ i ( x , y ; z ) .
x ^ , g ^ = argmin x , g 1 2 b ( A x + g ) 2 2 + τ x 1 s.t. g 0 , x 0 , D g = 0  outside low frequency support .
f ~ ( x ) = f ( t a n 1 ( x z ) ) .
p d 2 ( 1 z 1 1 z 2 ) λ NA 2 d λ p 1 z 1 1 z 2 4 λ p 2 ,