Method of reducing noise for combined images

Abstract

The method comprises: the Contourlet transformation is used to make the multi-scaling and multi-directional sparse decomposition for the inputted noisy image; making a noise reduction on Contourlet domain using Bayes shrinkage threshold value method; and getting the pre noise reduction image using Contourlet inverse transform; making further noise reduction for the pre noise reduction image using Wiener filter method to get final noise-reduced image. The invention can be used in optical imaging, target detection and security monitoring.

Description

technical field [0001] The invention relates to an image combination denoising method, which uses an image combination denoising method based on shift-invariant Contourlet (contour wavelet) transform domain denoising and Wiener (Wiener) filtering to remove the noise in the image to improve the image quality. quality. It is widely used in military and non-military fields such as optical imaging, target detection, security monitoring and other systems. Background technique [0002] Usually, the images we get are polluted by different degrees of noise. For subsequent further processing, it is necessary to perform noise reduction processing, filter out noise, and retain all feature information of the image as much as possible to improve the restoration quality of the image. At present, image noise reduction methods mainly include: spatial filtering, such as mean filtering and median filtering, and transform domain filtering, such as low-pass filtering. [0003] In the past twe...

AI Technical Summary

Problems solved by technology

However, the actual situation shows that this method cannot completely remove the noise, and a small amount of noise still remains in the denoised image, which affects the image quality, and further denoising processing is required

Images