Multiframe digital image denoising method based on space domain and time domain combination filtering

Abstract

The invention discloses a multiframe digital image denoising method based on space domain and time domain combination filtering. The method comprises the following steps of inputting multiframe digital images of a same scene, wherein the multiframe digital images are collected under a low illumination environment; selecting a clearest image from the multiframe images as an reference image; carrying out global and local registration on the multiframe images; taking the reference image as a reference, establishing a similar group which is similar to a local area in the reference image in the space domain and the time domain and using the similar group to carry out collaboration filtering on the local area in the reference image; using brightness information in the images after the filtering and pixel distribution information to successively carry out color correction and contrast enhancement on the images after the filtering so as to acquire the images after denoising. By using the method of the invention, influences of factors of a noise, a motion blur and the like in the digital images on image quality are effectively restrained; noise suppression is performed and simultaneously a detail texture in the images is effectively retained. The method can be used for increasing the image quality in a digital image acquisition device under the low illumination environment.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an image denoising method, which can be used for digital image preprocessing in the fields of consumer digital image acquisition equipment, medical images, astronomical images, and environmental change assessment. Background technique [0002] Image denoising is a hot issue in the field of image processing, and it is also a very challenging research direction. The noise in the image will hinder people's understanding of the image content. Using image denoising can effectively suppress the influence of noise in the image on the image quality, improve people's awareness of the image content, and further process the image. [0003] According to the characteristics and statistical characteristics of digital images, many scholars have proposed a variety of different denoising algorithms over the years. According to their implementation methods, they can be roughly...

AI Technical Summary

Problems solved by technology

For image denoising based on multiple frames in a low-light environment, in order to avoid motion blur in each frame image caused by long-time exposure, it is required that the collected multiple-frame images for the same scene must be within a short exposure time However, the shorter exposure time is bound to significantly increase the noise intensity in the image due to the reduction of the amount of incoming light.

In this case, how to effectively use the spatial and temporal similarity in multi-frame images to suppress the influence of noise is a very complex and challenging task.

In addition, the relative displacement between multi-frame images caused by the shake of the photographer's hand, and the local blurring of the image caused by local motion in the scene, all set obstacles for the use of multi-frame image denoising

Directly extend the existing single-frame image denoising method to multi-frame image denoising, because it does not make full use of the rich temporal information provided by multi-frame images, and at the same time cannot solve the above-mentioned multi-frame images. The impact of the relative displacement between them and the local motion in the scene on the image quality, so it is difficult to obtain the ideal denoising effect

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