Robust detector design based on Stochastic Resonance
Two potential applications of SR will be considered in this project. First, the SR detector will be used in digital watermarking in the DCT domain. The watermark information is considered as weak signal embedded in the DCT coefficients considered as noise. The statistics of the noise is difficult to estimate. The BS-detector provides a robust solution and the detection performance is expected to be improved significantly. Secondly, a SR detector will be used to detect features in MRI brain images. The MRI images do not have sharp features, and are noisy. It is difficult to detect small features (e.g., lesions or tumors) in an MRI image. We would investigate the use of SR detector in improving the feature detection performance.
The student will have a role both in theoretical development and experimental evaluation of the BS-SR detector, including the following three major tasks: The student will evaluate various measures of the BS performance for signal transmission, the student will investigate the relationship between the BS performance measure (MI or cross-correlation) and the BS system parameters, for given input signal and noise characteristics, the student will evaluate the efficacy of the developed performance measure by applying the SR detector in digital watermarking applications.