Abstract
Random valued impulse noise is removed in digital images, and an Improved Decision Based (IDB) filtering technique is proposed. The decision-based filtering algorithm’s function is to detect noisy pixels by making judgments in three different modules. Once the noisy pixel has been found, the noise is removed using a Hybrid Wiener Adaptive Centre Weighted Median filter. Comparing the existing decision tree-based approach, the suggested filter removes substantially more noise. The suggested modified decision tree method produces better outcomes for high-density noise levels of up to 90%, according to both visual and quantitative data.
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