Authors - Eshwari Khurd, Shravani Kamthankar, Avani Kelkar, Ravinder B. Yerram Abstract - One of the major challenges encountered when it comes to speech recognition, medical imaging, and multimedia processing for radar or weather forecasting applications, is noise interference in audio and image signals that invariably affect algorithmic precision and dependability. Denoising is responsible for removing unwanted noise while keeping intact the necessary details in the signal. An effective denoising method for audio and image signals is under continuous research across multiple parameters taken into consideration giving priority to signal-to-noise ratio (SNR). In this paper, we have surveyed various such denoising methods with a focus on the ones using Principal Component Analysis (PCA) and Ensemble Empirical Mode Decomposition (EEMD).
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