Deep Camera Obscura: An Image Restoration Pipeline for Lensless Pinhole Photography

The lensless pinhole camera is perhaps the earliest and simplest form of an imaging system using only a pinholesized aperture in place of a lens. They can capture an infinite depth-of-field and offer greater freedom from optical distortion over their lens-based counterparts. However, the inherent limitations of a pinhole system result in lower sharpness from blur caused by optical diffraction and higher noise levels due to low light throughput of the small aperture, requiring very long exposure times to capture well-exposed images. In this paper, we explore an image restoration pipeline using deep learning and domainknowledge of the pinhole system to enhance the pinhole image quality through a joint denoise and deblur approach. Our approach allows for more practical exposure times for hand-held photography and provides higher image quality, making it more suitable for daily photography compared to other lensless cameras while keeping size and cost low. This opens up the potential of pinhole cameras to be used in smaller devices, such as smartphones.

[1]  S. Nayar,et al.  What are good apertures for defocus deblurring? , 2009, 2009 IEEE International Conference on Computational Photography (ICCP).

[2]  Laura Waller,et al.  DiffuserCam: Lensless Single-exposure 3D Imaging , 2017, ArXiv.

[3]  Michal Irani,et al.  Blind Deblurring Using Internal Patch Recurrence , 2014, ECCV.

[4]  Richard G. Baraniuk,et al.  Face Detection and Verification Using Lensless Cameras , 2019, IEEE Transactions on Computational Imaging.

[5]  D. Narmadha,et al.  A Survey on Image Denoising Techniques , 2012 .

[6]  Lei Zhang,et al.  FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising , 2017, IEEE Transactions on Image Processing.

[7]  Alyosha Molnar,et al.  A microscale camera using direct Fourier-domain scene capture. , 2011, Optics letters.

[8]  P A Newman,et al.  Pinhole array camera for integrated circuits. , 1966, Applied optics.

[9]  Michael S. Bernstein,et al.  ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.

[10]  Lei Zhang,et al.  Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising , 2016, IEEE Transactions on Image Processing.

[11]  Ashok Veeraraghavan,et al.  PhaseCam3D — Learning Phase Masks for Passive Single View Depth Estimation , 2019, 2019 IEEE International Conference on Computational Photography (ICCP).

[12]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[13]  K. Egiazarian,et al.  Blind image deconvolution , 2007 .

[14]  Orly Liba,et al.  Handheld mobile photography in very low light , 2019, ACM Trans. Graph..

[15]  Suren Jayasuriya,et al.  Robust Lensless Image Reconstruction via PSF Estimation , 2021, 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).

[16]  Michael S. Brown,et al.  Noise Flow: Noise Modeling With Conditional Normalizing Flows , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[17]  Antonio Torralba,et al.  Accidental Pinhole and Pinspeck Cameras , 2014, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[18]  Ick,et al.  DiffuserCam : Lensless Single-exposure 3 D Imaging , 2017 .

[19]  Jean-Michel Morel,et al.  A non-local algorithm for image denoising , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[20]  Jonathan T. Barron,et al.  Burst photography for high dynamic range and low-light imaging on mobile cameras , 2016, ACM Trans. Graph..

[21]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[22]  Shuai Li,et al.  Lensless computational imaging through deep learning , 2017, ArXiv.

[23]  Jia Xu,et al.  Learning to See in the Dark , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[24]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[25]  Wangmeng Zuo,et al.  Toward Convolutional Blind Denoising of Real Photographs , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  Wangmeng Zuo,et al.  Learning Deep CNN Denoiser Prior for Image Restoration , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[27]  Jitendra Malik,et al.  Recovering high dynamic range radiance maps from photographs , 1997, SIGGRAPH '08.

[28]  Alessandro Foi,et al.  Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.

[29]  Jan Kautz,et al.  Reblur2Deblur: Deblurring videos via self-supervised learning , 2018, 2018 IEEE International Conference on Computational Photography (ICCP).

[30]  Seungyong Lee,et al.  Fast motion deblurring , 2009, ACM Trans. Graph..

[31]  Laura Waller,et al.  Learned reconstructions for practical mask-based lensless imaging , 2019, Optics express.

[32]  Zhangyang Wang,et al.  DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[33]  A. Nehorai,et al.  Deconvolution methods for 3-D fluorescence microscopy images , 2006, IEEE Signal Processing Magazine.

[34]  Shree K. Nayar,et al.  Motion-based motion deblurring , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  M Young Pinhole optics. , 1971, Applied optics.

[36]  Julie Delon,et al.  An Analysis and Implementation of the FFDNet Image Denoising Method , 2019, Image Process. Line.

[37]  Stephen Lin,et al.  Coded Aperture Pairs for Depth from Defocus and Defocus Deblurring , 2011, International Journal of Computer Vision.

[38]  Salman Siddique Khan,et al.  FlatNet: Towards Photorealistic Scene Reconstruction From Lensless Measurements , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[39]  Li Xu,et al.  Unnatural L0 Sparse Representation for Natural Image Deblurring , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[40]  J. Ponce,et al.  End-to-end Interpretable Learning of Non-blind Image Deblurring , 2020, ECCV.

[41]  Kaushik Mitra,et al.  Towards Photorealistic Reconstruction of Highly Multiplexed Lensless Images , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[42]  Aswin C. Sankaranarayanan,et al.  FlatCam: Thin, Lensless Cameras Using Coded Aperture and Computation , 2017, IEEE Transactions on Computational Imaging.

[43]  Abbas El Gamal,et al.  Comparative analysis of SNR for image sensors with enhanced dynamic range , 1999, Electronic Imaging.

[44]  J. H. Hammond The Camera Obscura, A Chronicle , 1981 .

[45]  Jean-Michel Morel,et al.  A Nonlocal Bayesian Image Denoising Algorithm , 2013, SIAM J. Imaging Sci..

[46]  Gordon Wetzstein,et al.  A switchable light field camera architecture with Angle Sensitive Pixels and dictionary-based sparse coding , 2014, 2014 IEEE International Conference on Computational Photography (ICCP).

[47]  Peter F. Sturm,et al.  Pinhole Camera Model , 2014, Computer Vision, A Reference Guide.

[48]  George Barbastathis,et al.  Imaging through glass diffusers using densely connected convolutional networks , 2017, Optica.

[49]  David G. Stork,et al.  Lensless Ultra-Miniature Imagers Using Odd-Symmetry Spiral Phase Gratings , 2013 .

[50]  Jiri Matas,et al.  DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[51]  Portable X-ray and gamma-ray imager with coded mask: performance characteristics and methods of image reconstruction , 1999 .

[52]  Subhasis Chaudhuri,et al.  Blind Image Deconvolution , 2014, Springer International Publishing.

[53]  Gengsheng Chen,et al.  Scale-Iterative Upscaling Network for Image Deblurring , 2020, IEEE Access.

[54]  Yusuke Nakamura,et al.  Lensless light-field imaging with multi-phased fresnel zone aperture , 2017, 2017 IEEE International Conference on Computational Photography (ICCP).

[55]  Hongdong Li,et al.  Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[56]  Michael S. Brown,et al.  Defocus Deblurring Using Dual-Pixel Data , 2020, ECCV.

[57]  Jacob T. Robinson,et al.  PhlatCam: Designed Phase-Mask Based Thin Lensless Camera , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[58]  D. Malacara-Hernández,et al.  PRINCIPLES OF OPTICS , 2011 .

[59]  J. Goodman Introduction to Fourier optics , 1969 .

[60]  Ayan Chakrabarti,et al.  A Neural Approach to Blind Motion Deblurring , 2016, ECCV.

[61]  J. Tanida,et al.  Thin Observation Module by Bound Optics (TOMBO): Concept and Experimental Verification. , 2001, Applied optics.

[62]  Antonio Torralba,et al.  Accidental pinhole and pinspeck cameras: Revealing the scene outside the picture , 2012, CVPR.

[63]  Lei Tian,et al.  Deep speckle correlation: a deep learning approach toward scalable imaging through scattering media , 2018, Optica.

[64]  Richard E. Swing,et al.  General Transfer Function for the Pinhole Camera , 1968 .

[65]  Jérôme Primot,et al.  Compact infrared pinhole fisheye for wide field applications. , 2009, Applied optics.