DWT is a promising approach for biomedical image compression that may produce visually pleasing results by mimicking primitive models of the human visual system.
DWT applications in health signals warrant validation; leaves open clinical adoption.
The Discrete Wavelet Transform (DWT) is a unique signal analysis approach that has been actively applied to a range of difficulties in image processing in recent years. Windowing with varying area sizes is what makes it so powerful. DWT allows us to use small areas where we want high-frequency information more effectively. Wavelet research has picked up steam in the last few years. When it comes to digital signal processing and communication, DWT can be used in a variety of ways. As a voice and picture coding technology, it has many of the characteristics of primitive models of the human visual system. When this is taken into account, it is possible that coding methods will produce compression that is more pleasing to the eye than those that aim to minimise square error. Patterns and breakdown points can be revealed in data using DWT, which other approaches miss. DWT is becoming increasingly popular and is the subject of extensive research, in part because of its many advantages.
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Ramaprakash et al. (2022) studied this question.
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