Structured illumination optical super-resolution with space-variant perspective imaging systems,” Prasanna Rangarajan, Indranil Sinharoy, Manjunath Somayaji, Vikrant R. Bhakta, Predrag Milojkovic and Marc P. Christensen. [Currently as manuscript, in preparation for submission to Optics Express]



"Omnifocus" Omnifocus image synthesis using Lens Swivel,” Indranil Sinharoy, Prasanna Rangarajan, Marc P. Christensen, OSA Topical meeting on Imaging Systems & Applications, 2016.


"CFASFR" A critical review of the slanted-edge method for color SFR measurement,” Prasanna Rangarajan, Indranil Sinharoy, Marc P. Christensen, Predrag Milojkovic, OSA Topical meeting on Imaging Systems & Applications, 2012.


"Pushing the limits of Imaging" Pushing the limits of digital imaging using Structured Illumination,” Prasanna Rangarajan, Indranil Sinharoy, Panos Papamichalis, Marc P. Christensen , Proc. 13th IEEE International Conference on Computer Vision, ICCV 2011.

"Space variant optical super resolution"Space-Variant Optical Super-Resolution using Sinusoidal Illumination,” Prasanna Rangarajan, Vikrant R. Bhakta, Indranil Sinharoy, Manjunath Somayaji and Marc P. Christensen, Computational Optical Sensing and Imaging (COSI),Toronto, Canada, July, 2011.


"Saliency map" Model-Based Region-Of-Interest estimation for adaptive resource allocation in multi-aperture imaging systems,” Indranil Sinharoy, Scott C. Douglas, Dinesh Rajan, Marc P. Christensen, IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP), Las Vegas, Nevada,pp. 1961-1964, Apr. 2008.


"Adaptive Resource Allocation"
Region-of-interest estimation for adaptive resource allocation in multi-aperture imaging systems,” I. Sinharoy, S.C. Douglas, IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP), Honolulu, HI, vol. 2, pp. 597-600, Apr. 2007.



"Region of interest estimation and adaptive resource allocation"Region-of-interest estimation for adaptive resource allocation in multi-aperture imaging systems,” Indranil Sinharoy, Southern Methodist University, December 2006.(Master’s thesis)

Scaling down traditional optical imaging systems to enhance their form factor presents fundamental challenges in terms of loss of resolution and a decrease in the optical SNR due to the reduced light gathering ability of such scaled imagers. Computational imaging systems can address these issues through joint optimization of their optics and signal processing subsystems. One class of computational imagers is the thin, flat-profile multiplexed imaging system, which uses a combination of several scaled individual imaging units to capture a number of low-resolution images that are then digitally processed to reconstruct a high resolution version of the observed scene.
The performance of multiplexed imagers may be enhanced through the use of adaptive techniques wherein imager resource utilization is maximized through intelligent resource allocation based on the information content in the scene. The body of work laid out in this thesis describes techniques to find regions of interest in a scene and serves to enhance the efficiency of resource allocation in adaptive multiplexed imaging systems. The power spectral density (PSD) is used to derive local entropy maps of input scenes towards identification of regions of interest. Empirical evidence supporting the superiority of PSD-based saliency maps over their histogram-based counterparts in terms of relative local saliency representation of various regions within a scene is provided. Statistical analysis of noise in a scientific-grade digital camera shows that the noise power in images increased with pixel intensity indicating Poisson noise characteristics. A numerically fast and efficient method for computing model-based local saliency maps is presented, and its performance is evaluated in terms of the number of adders, multipliers and table lookups.


Non-peer reviewed papers, technical articles, pre-prints.


Geometric model of image formation in Scheimpflug cameras,” Indranil Sinharoy, Prasanna Rangarajan, and Marc P. Christensen, PeerJ Preprints 4:e1887v1.


Array ray tracing in Zemax OpticStudio from Python using the DDE extension,” Indranil Sinharoy, Knowledgebase article for Zemax.


Talking to ZEMAX from Python using PyZDDE,” Indranil Sinharoy, Knowledgebase article for Zemax.


Image Denoising Using Modified Neighshrink Algorithm,” Indranil Sinharoy, Tech. Report, Southern Methodist University 2012.

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