Abstract
Recent research efforts have explored methods to achieve the wavelet transform as the most significant tool in medical image enhancement and processing. The problems of image fusion, compression, edge detection, denoising, and contrast enhancement can be handled by discrete wavelet transform (DWT) in the Internet of medical things (IoMT) framework. In this chapter, we present the novel DWT with orthogonal and biorthogonal wavelets application. Multiple applications of the wavelet transform in medical images have been submitted. These applications demonstrate the successful impact of applying DWT. The DWT has the ability to enhance the medical image and remove noise. The DWT in image compression can separately reduce the computational complexity into high and low frequency. This process reduces the image data in order to be able to store or transmit data in an efficient form. There are some advantages in using fusion based on DWT during other traditional methods, for example, reduced features and energy compaction. In digital watermarking, DWT technique is used for embedding and extraction of watermark in the original image.
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