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[[File:SPAD EPFL BINARY IMAGES.jpg|thumb|right|255px|Fig.4 Reconstructing an image from the binary measurements taken by a SPAD<ref name="SPADS">L. Carrara, C. Niclass, N. Scheidegger, H. Shea, and E. Charbon, A gamma, X-ray and high energy proton radiation-tolerant CMOS image sensor for space applications, in ''IEEE International Solid-State Circuits Conference, Feb. 2009, pp.40-41.</ref> sensor, with a spatial resolution of 32×32 pixels. The final image (lower-right corner) is obtained by incorporating 4096 consecutive frames, 11 of which are shown in the figure.]]
One of the most important challenges with the use of an oversampled binary image sensor is the reconstruction of the light intensity <math>\lambda(x)</math> from the binary measurement <math>b_m</math>. [[Maximum likelihood|Maximum likelihood estimation]] can be used for solving this problem.<ref name="bitsfromphotons" /> Fig. 4 shows the results of reconstructing the light intensity from 4096 binary images taken by [[single photon avalanche diode]]s (SPADs) camera.<ref name="SPADS" /> A Better reconstruction quality with fewer temporal measurements and faster, hardware friendly implementation, can be achieved by more sophisticated algorithms.<ref>{{Cite journal|title = Image reconstruction from dense binary pixels|url = http://arxiv.org/abs/1512.01774|journal = arXiv:1512.01774 [cs]|date = 2015-12-06|first = Or|last = Litany|first2 = Tal|last2 = Remez|first3 = Alex|last3 = Bronstein}}</ref>
== References ==
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