FlatCam is a thin form-factor lensless camera that consists of a coded mask placed on top of a bare, conventional sensor array. Unlike a traditional, lens-based camera where an image of the scene is directly recorded on the sensor pixels, each pixel in FlatCam records a linear combination of light from multiple scene elements. A computational algorithm is then used to demultiplex the recorded measurements and reconstruct an image of the scene. FlatCam is an instance of a coded aperture imaging system; however, unlike the vast majority of related work, we place the coded mask extremely close to the image sensor that can enable a thin system. We employ a separable mask to ensure that both calibration and image reconstruction are scalable in terms of memory requirements and computational complexity. We demonstrate the potential of the FlatCam design using two prototypes: one at visible wavelengths and one at infrared wavelengths.

We report Giga-pixel lensfree holographic microscopy and tomography using color sensor-arrays such as CMOS imagers that exhibit Bayer color filter patterns. Without physically removing these color filters coated on the sensor chip, we synthesize pixel super-resolved lensfree holograms, which are then reconstructed to achieve,350 nm lateral resolution, corresponding to a numerical aperture of,0.8, across a field-of-view of,20.5 mm2. This constitutes a digital image with,0.7 Billion effective pixels in both amplitude and phase channels (i.e.,,1.4 Giga-pixels total). Furthermore, by changing the illumination angle (e.g.,650u) and scanning a partially-coherent light source across two orthogonal axes, super-resolved images of the same specimen from different viewing angles are created, which are then digitally combined to synthesize tomographic images of the object. Using this dual-axis lensfree tomographic imager running on a color sensor-chip, we achieve a 3D spatial resolution of,0.35 mm60.35 mm6,2 mm, in x, y and z, respectively, creating an effective voxel size of,0.03 mm3 across a sample volume of,5 mm3, which is equivalent to.150 Billion voxels. We demonstrate the proof-of-concept of this lensfree optical tomographic microscopy platform on a color CMOS image sensor by creating tomograms of

FlatCam is a thin form-factor lensless camera that consists of a coded mask placed on top of a bare, conventional sensor array. Unlike a traditional, lens-based camera where an image of the scene is directly recorded on the sensor pixels, each pixel in FlatCam records a linear combination of light from multiple scene elements. A computational algorithm is then used to demultiplex the recorded measurements and reconstruct an image of the scene. FlatCam is an instance of a coded aperture imaging system; however, unlike the vast majority of related work, we place the coded mask extremely close to the image sensor that can enable a thin system. We employ a separable mask to ensure that both calibration and image reconstruction are scalable in terms of memory requirements and computational complexity. We demonstrate the potential of the FlatCam design using two prototypes: one at visible wavelengths and one at infrared wavelengths. I.

Abstract—We review traditions and trends in optics and imag-ing recently arising by applying programmable optical devices or by sophisticated approaches for data evaluation and image reconstruction. Furthermore, a short overview is given about modeling of well-known classical optical elements, and vice versa, about optical realizations of classical mathematical transforms, as in particular Fourier, Hilbert, and Riesz transforms. I.

ith researchers ' ever-increasing interest in observing the nano-scale world and in controlling light at wavelength-scale dimensions and smaller, micro- and nano-optical elements are gaining widespread use. Applications include high-resolution lithography,1,2 extreme minia-turization of couplers and interconnects in photonic circuits,3 spatial control of surface plasmon polaritons,4,5 sensitivity enhance-ment for CCD and CMOS image sensors,6 emissivity enhancement for LEDs,7 near-field imaging for subdiffraction-limit resolution,810 and sensitivity enhancement in detection of nanoparticles and viruses.1113 In each of

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By submitting this dissertation electronically, I declare that the entirety of the work con-tained therein is my own, original work, that I am the sole author thereof (save to the extent explicitly otherwise stated), that reproduction and publication thereof by Stellen-bosch University will not infringe any third party rights and that I have not previously in its entirety or in part submitted it for obtaining any qualification.