A novel method based on adaptive median filtering and wavelet transform in noise images
Ying Ma, Junshan Li · 2011
An image is often corrupted by much noise visible or invisible while being collected, acquired, coded and transmitted. Noise impairs the quality of the received image severely and may cause a big problem for further image processing. In order to improve the quality of an image, the noise must be removed when the image is preprocessed, and the important signal features should be retained as much as possible. The methodology of image denoising is studied in this paper base on median filter and wavelet theory, in the setting of additive salt and pepper noise or white Gaussian noise. In the first phase, Canny edge detection is used in edge detection of the noise image to get the basic outline; In the second phase, an ameliorative adaptive median filter(adaptive variational threshold value) is used to remove salt noise; In the third phase, Coiflet wavelet system used to remove pepper noise; at last, processing images linking to get final images.