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Some examples on compressed sensing, inspired by the single pixel camera

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Compressed-Sensing

Some examples on compressed sensing, inspired by the single pixel camera.

Sine Wave Reconstruction

The first example contains a superposition of sine waves (blue) and a set of measurements (red). From these values a reconstruction (green) is generated.

Note that the number of measurements is far below the limit we get from the Nyquist-Shannon sampling theorem.

sine_wave_reconstruction

Simple Image Reconstruction

The second example contains a simple picture of a white blob on black background (right) and a reconstruction from random measurements (left), which represents the way the single pixel camera works.

ball ball_reconstruction

Lena Reconstruction

No work with images is complete without Lena. So I did the same procedure as in the second example but with the usual Lena picture.

The result is a recognizable reconstruction of the original, but not entirely satisfying. I blame the optimization algorithm ¯\_(ツ)_/¯.

lena lena_reconstruction

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