Medical Signal Denoising Using Wavelet Transform

Abstract

Images and videos have turned into a part of our life in the recent past. Applications now range from more general event documentation and visual communication to more serious surveillance and medicine. This has increased the huge demand for images of high accuracy and visual quality. But digital images obtained from modern cameras tend to become corrupted by noise during the process of image acquisition (digitization) and/or transmission. This type of corruption can lead to deterioration of visual quality of an image. The effectiveness of imaging sensors is influenced by a variety of factors, including conditions during the time of image capture and by sensing element quality itself. For instance, while acquiring images using a CCD camera, sensor temperatures and light intensities are significant parameters that can influence the level of noise in the acquired image. Corruption in images can also take place during transmission. Reason being the channel interference used for transmission. For instance, an image transmitted via a wireless medium could be corrupted due to lighting effects or other atmospheric interference. Image denoising is a topic which has been well researched under image processing with the main aim to enhance the visual quality of an image by removing noise from its provided noisy form. There have been a variety of techniques for image denoising designed to reduce the impact of the noise(s) caused due to any of the aforementioned sources of noise. The primary challenge is to maintain the details of the image and local geometries while eliminating the unwanted noise.