Mean filtering is a fundamental digital signal processing technique commonly used for image and signal denoising. This article will detail how to implement a simple yet efficient mean filter using the Verilog hardware description language.
Basic Principles of Mean Filtering
The core idea of mean filtering is to replace the value of a pixel with the average value of its surrounding neighborhood. For a 3×3 neighborhood, the calculation formula is as follows:
This method can effectively reduce random noise but may cause slight blurring of image edges.Implementation Method
Design Description
This mean filter implementation includes the following key components:
Row Buffer Mechanism：Two row buffers are used to store the previous two rows of data, along with the current row data to form a 3×3 window.
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3×3 Window Construction：Using pixel buffers and row buffers, extract the 9 pixel values surrounding the currently processed pixel.
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Summation and Average Calculation：Add the 9 pixel values and divide by 9 to obtain the average. Here, a right shift of 3 bits (dividing by 8) is used as an approximation to dividing by 9 to improve hardware efficiency.
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Pipelined Design：To enhance processing speed, a pipelined structure is adopted, ensuring that one pixel can be processed per clock cycle.
Processing Results:
Original Image
Image After Mean Filtering
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