This paper studies the optimal bit error rate (BER) performance of chip-level detection for optical code division multiple-access (OCDMA) systems in the presence of shot noise. To attain the optimal BER of chip-level detection, a chip-level detector that uses a limiter on the photon counts at each weighted chip is first proposed. Then, the monotonicity of the likelihood ratio used in the maximum a posteriori (MAP) probability criterion is established. With this monotonicity, a sufficient condition characterized by the cap levels of the limiters and the average photon counts per pulse is obtained, under which the detector is simply an AND detector to attain the optimal BER of chip-level detection. The detector' performance and its comparison to those of other detectors are also studied by numerical studies.

With radio-over-fiber (RoF) enabled remote antenna, gigabit Ethernet service operating at 60-GHz frequencies can be accessed cordlessly. Due to limited linear operation region of 60-GHz optoelectronic modulators commercially available so far, optical weak modulation is required leading to limited link performance. This paper demonstrates in RoF transmission of 1.25-Gigabit Ethernet signal on 60-GHz band subcarrier, the fiber downlink performance is improved by suppressing the optical carrier-to-sideband ratio based on the usage of a simple and low-cost fabricated 2 times 2 all-fiber optical interleaver. Simultaneously by using the interleaver, the downlink optical carrier is recovered and is reused as optical source for fiber uplink hence laser-free access point is achieved.

In this paper, the monotonicity of the likelihood ratio used in the optimal correlation detection is established for optical code division multiple-access (OCDMA). The monotonicity property not only guarantees the optimality of the detection, it also enables us to calculate the bit-error-rate bounds for OCDMA in the presence of uncertain a priori probabilities.

In practical computer vision system, there are situations where displacement of an image is accompanied by a defocus blur. Since depth can be estimated from the degree of blur, in this paper we propose a method to get the blur parameter and simultaneously affine transformation parameters. Firstly we introduce a method to get the motion parameters from the original image and the affine transformed and simultaneously blurred image (second image). Then we use these parameters to construct affine transformed image. The last step is to get the blur parameters from the constructed image and the second image. The effectiveness of the proposed method is demonstrated by experimental results.