To classify the significant wavelet coefficients into edge area and noise area, a morphological clustering filter applied to wavelet shrinkage is introduced. New methods for wavelet shrinkage using morphological clustering filter are used in noise removal, and the performance is evaluated under various noise conditions.

In this paper, we present a minimum-maximum exclusive weighted-mean filtering algorithm with adaptive window. Image pixels within the varying size of the window are ranked and classified as minimum-maximum and median levels, and then passed through the weighted-mean of median level and identity filters, respectively. The filtering window size is adaptively increasing according to noise ratio without noise measurement. Extensive simulations show that the proposed filter performs better than other median/rank-type filters in removing impulse noise of highly corrupted images.

In this paper, we present improved alternative sequential filter-edge detector using generalized directional morphological filters. Based on the properties of effective noise removal and detail preservation of the generalized directional morphological filters, we apply these filters to edge detection of noisy images. The performance of the edge detection in the presence of mixed noise is evaluated. Simulations show that edge detection method using generalized directional morphological filters can also improve the performance.

In this paper, we present a new frequency identification technique using the recent methodology of compressive sensing and discrete prolate spheroidal sequences with optimal energy concentration. Using the bandpass form of discrete prolate spheroidal sequences as basis matrix in compressive sensing, compressive frequency sensing algorithm is presented. Simulation results are given to present the effectiveness of the proposed technique for application to detection of carrier-frequency type signal and recognition of wideband signal in communication.

In this paper, we present a directional interpolation filter in which the minimum and maximum pixels in the given window are excluded. Image pixels within a predefined window are ranked and classified as minimum-maximum or exclusive level, and then passed through the interpolation and identity filters, respectively. Extensive simulations show that the proposed filter performs better than other nonlinear filters in preserving desired image features while reducing impulse noise effectively.

In this paper, we present the design and implementation of a cost effective Ethernet over HDLC forwarding VLSI for network access system. It supports 10/100 Mbps Ethernet PHYs and up to 50 Mbps HDLC interface directly applied to Modem or transceiver. The maximum forwarding/filtering rate is 90,000 pps with a throughput latency of 1 frame, which supports high speed applications. It can also support both master mode for Ethernet PHY and slave mode for switching chip by the pin configuration. It has been implemented as a single chip based on 0.5 µm CMOS technology. Field test shows that the wire-speed packet forwarding and processing using by the implemented chip can be achieved.