A two-stage algorithm, called switching-based adaptive weighted mean filter, is proposed to remove salt-and-pepper noise from the corrupted images. First, the directional difference based noise detector is used to identify the noisy pixels by comparing the minimum absolute value of four mean differences between the current pixel and its neighbors in four directional windows with a predefined threshold. Then, the adaptive weighted mean filter is adopted to remove the detected impulses by replacing each noisy pixel with the weighted mean of its noise-free neighbors in the filtering window. Numerous simulations demonstrate that the proposed filter outperforms many other existing algorithms in terms of effectiveness in noise detection, image restoration and computational efficiency.

Impulse Noise Removal Using Directional Difference Based Noise Detector and Adaptive Weighted Mean Filter

Real-time imaging has application in areas such as multimedia, virtual reality, medical imaging, and remote sensing and control. Recently, the imaging community has witnessed a tremendous growth in research and new ideas in these areas. To lend structure to this growth, we outline a classification scheme and provide an overview of current research in real-time imaging. For convenience, we have categorized references by research area and application.

Classification and overview of research in real-time imaging

A new modified 2D (3*3) multi-shell median filter (MMMF) for restoration of images corrupted with impulse noise is presented. This filter can not only reduce impulse noise but alleviate missing line errors. The hardware of MMMF can be easily implemented using standard TTL ICs. In fact, we realize the circuit by the Field Programmable Gate Array (FPGA). This novel median filter can be used in a real time system for noise suppression. >

Modified 2D median filter for impulse noise suppression in a real-time system

In this paper, we propose a fast algorithm to realize parallel median filter for processing 1-D and 2-D signal. In the proposed pipelined architecture, m-passes are employed for filtering signal while word resolution is m bits. One pass employs one processing element (PE), and the number of PEs is independent of the number of samples. Therefore, we only need m PEs for real-time operation. With 8-bits resolution, the system gate-count is less than 5 k. Moreover, this median architecture could be easily modified to consist of the programmable feature that may choose the better sampling number to filter signal. It should be also noted that our proposed processing flow has a progressive property, which is very suitable for bandwidth-limited channel application. key words: median lter, processing element, programmable,

A Parallel Median Filter with Pipelined Scheduling for Real-Time 1D and 2D Signal Processing

It is shown that for a particular window size, by changing gradually the minimum and maximum operators to the higher and lower order statistics of the shell, respectively, the multi-shell median filter will gradually turn from a multistage max/median filter into a 2-D standard median filter. >

The relationship of the multi-shell to multistage and standard median filters

A 2-D, multishell median-based filter for real-time video signal processing is presented. The device is able to remove impulse and missing line noise in real-time without blurring sharp video images. A prototype using 75 standard transistor-transistor logic (TTL) chips has been realized on one single speedwire prototype board of size 17*30 cm/sup 2/ and its structure is suitable for VLSI implementation. The statistical performance of the nonlinear filter has been investigated and compared with that of standard 2-D median filters. It is shown that the filter has characteristics superior to those of its median-based counterparts while the hardware implementation is much simpler. >

S. Luthi

Papers

A real-time 2-D median based filter for video signals