We propose a statistical technique for autonomously detecting defective pixels in a CCD sensor array. Our data-driven
analysis technique can autonomously identify a wide range of faulty and 'suspect' pixels (hypo-sensitive
or hyper-sensitive pixels), without the need for any defect model or prior knowledge of the nature of pixel faults.
We apply our technique to the autonomous detection of the defective pixels in regular images captured with a
camera, equipped with a CCD.
We report measurements of the near-field pattern of ridge-waveguide tunnel injection In0.4Ga0.6As/GaAs self-assembled quantum dot lasers and have compared the results with similar strained quantum well lasers. While no filamentation is observed in the quantum dot devices, significant filamentatin and side lobes are observed in the quantum well lasers. The trend is corroborated by measured linewidth enhancement factor, α, of the two types of devices. Values of α~3.8 are measured in the quantum well lasers, while α is ≤0.7 in the quantum dot lasers, suggesting a very small refractive index change with injection in the active region. Chirp ≤0.6Å is measured in the tunnel injection devices, while it varies in the 1.6-3 Å range in the quantum well lasers.