Towards Improving Performance of Sigma Filter

Sigma filter is one of the widely used filters for noise removal. This is popular because of its simple implementation and computationally in-expensiveness and better filtering accuracy than many other existing filters. In this work, we have proposed an improved Sigma filter, where the filtering method is separately applied to high- and low-frequency segments of the image and then restored image is constructed by combining the two filtered images. The basic assumption of this work is the fact that effect of noise is different on high-frequency (more) and low-frequency (analogously less) segments of the image and hence more amount of noise can be removed by separately applying a noise removal filter on high- and low-frequency segments of the image. Comparative results between the proposed noise removal filter and other noise removal filters show that proposed noise removal filter is capable of removing noise from images without affecting their visual details.

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