Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications

The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well

Retinal Imaging: Acquisition, Processing, and Application of Mueller Matrix Confocal Scanning Laser Polarimetry

The focus of this thesis is the improvement of acquisition and processing of Mueller matrix polarimetry using a confocal scanning laser ophthalmoscope (CSLO) and the application of Mueller matrix polarimetry to image the retina. Stepper motors were incorporated into a CSLO to semi-automate Mueller matrix polarimetry and were used in retinal image acquisition. Success rates of Fourier transform based edge detection filters, designed to improve the registration of retinal images, were compared. The acquired polarimetry images were used to reassess 2 image quality enhancement techniques, Mueller matrix reconstruction (MMR) and Stokes vector reconstruction (SVR), focusing on the role of auto-contrasting or normalization within the techniques and the degree to which auto-contrasting or normalization is responsible for image quality improvement of the resulting images. Mueller matrix polarimetry was also applied to find the retardance image of a malaria infected retinal blood vessel imaged in a confocal scanning laser microscope (CSLM) to visualize hemozoin within the vessel. Image quality enhancement techniques were also applied and image quality improvement was quantified for this blood vessel. The semi-automation of Mueller matrix polarimetry yielded a significant reduction in experimental acquisition time (80%) and a non-significant reduction in registration time (44%). A larger sample size would give higher power and this result might become significant. The reduction in registration time was most likely due to less movement of the eye, particularly in terms of decreased rotation seen between registered images. Fourier transform edge detection methods increased the success rate of registration from 73.9% to 92.3%. Assessment of the 2 MMR images (max entropy and max signal-to-noise ratio (SNR)) showed that comparison to the best CSLO images (not auto-contrasted) yielded significant average image quality improvements of 158% and 4% when quantified with entropy and SNR, respectively. When compared to best auto-contrasted CSLO images, significant image quality improvements were 11% and 5% for entropy and SNR, respectively. Images constructed from auto-contrasted input images were of significantly higher quality than images reconstructed from original images. Of the 2 other images assessed (modified degree of polarization (DOPM) and the first element of the Stokes vector (S0)), DOPM and S0 yielded significant average image quality improvements quantified by entropy except for the DOPM image of the RNFL. SNR was not improved significantly when either SVR image was compared to the best CSLO images. Compared to the best auto-contrasted CSLO images, neither DOPM nor S0 improved average image quality significantly. This result might change with a larger number of participants. When MMR were applied to images of malaria infected retinal slides, image quality was improved by 19.7% and 15.3% in terms of entropy and SNR, respectively, when compared to the best CSLO image. The DOPM image yielded image quality improvements of 8.6% and -24.3% and the S0 image gave improvements of 9.5% and 9.4% in entropy and SNR, respectively. Although percent increase in image quality was reduced when images were compared to initial auto-contrasted CSLO images, the final image quality was improved when auto-contrasting occurred prior to polarimetry calculations for max SNR and max entropy images. Quantitative values of retardance could not be found due to physical constraints in the CSLM that did not allow for characterization of its polarization properties and vibrational noise. Mueller matrix polarimetry used to find the retardance image of a malaria infected retina sample did yield visualization of hemozoin within the vessel but only qualitatively. In conclusion, improvements in the acquisition and registration of CSLO images were successful in leading to considerably shorter experimentation and processing times. In terms of polarimetric image quality improvement techniques, when compared to the best CSLO image. A large proportion of the improvement was in fact due to partially or completely stretching the pixel values across the dynamic range of the images within the algorithm of each technique. However, in general the image quality was still improved by the Mueller matrix reconstruction techniques using both entropy and SNR to generate the CSLO retinal images and the CSLM imaged malaria infected sample. In the malaria sample, retinal blood vessel visualization was also qualitatively improved. The images yielded from Mueller matrix polarimetry applied to a malaria infected retinal sample localized hemozoin within the blood vessel, but a quantitative image of the phase retardance could not be achieved