Enhancing Signal in Noisy Environment: A Review

Abstract

Noise is present in all environments. In the signal processing domain also, there is a presence of noise. In any application, after processing, we need a signal which is free from noise. So to obtain a high-quality signal, elimination and reduction of noise are important. The different noises include Salt-Pepper, Gaussian, Speckle, Poisson, etc. So in order to eliminate this noise, some of the noise reduction techniques or filters can be employed in between. This survey paper presents the elimination of noise in images during duct, rain, snow, etc., elimination of noise in speech signals or mobile audio in high noisy environment such as conferences, meetings, heavy traffic conditions, and elimination of noise in biomedical signals in the presence of other noisy signals. For this purpose, many filtering techniques can be used, and depending on the filtered image obtained, we can find out which is best suited for the specific purpose.

Automatic classification and diagnosis of heart valve diseases using heart sounds with MFCC and proposed deep model

“…$$ M is the desired number of filters, and f () is the list of f , M + 2 Mel‐spaced frequencies. When utilized in speech signal processing, MFCC perform well against noisy signals, therefore they can also be used in biomedical signal processing 12,17 . The MFCC feature processing process is shown in Figure 4.…”