An Improved Wavelet Threshold Function And Its Application In Image Edge Detection

Abstract

In order to filter out image noise better and make it have better clarity, continuity and anti-noise performance in image edge extraction. Firstly, this paper constructs a new threshold function, compared with the traditional soft and hard threshold function and some existing improved methods, the threshold function has better adjustability and it is also continuous and almost smooth everywhere. When dealing with the wavelet coefficients, the real information on them can be retained more, and the noise can be effectively filtered at the same time. The simulation experiment shows that the image processed by the new threshold function has a high PSNR and a small MSE, which can be closer to the original image. Finally, the improved threshold function de-noising algorithm and the dyadic wavelet transform modulus maximum edge detection algorithm are combined to apply to image edge detection. By combining the advantages of the two algorithms, so that we can get clearer and more continuous image edges, and the contour is more complete.