An Improved Algorithm of Noise Elimination to Image Threshold

Image noise often affects the clarity of the image, resulting in image blurring. In order to better remove the image noise, especially the rich details in the image to remove noise in the area, the traditional denoising method is usually difficult to complete. To solve this problem, in order to better remove the image noise, preserving image details. In the classical wavelet soft and hard threshold denoising method based on a wavelet packet analysis based on improved methods. Wavelet packet transform is a time-frequency analysis, frequency analysis is better than the wavelet transform will be applied to image noise cancellation. Mat lab simulation results show that this method overcomes the shortcomings of the traditional threshold method to effectively improve the image to remove noise, higher resolution, and its noise cancellation effect is better than the wavelet denoising method. Wavelet packet transformation is a method for analysis of relations between time and frequency.