A method and device for self-adaptive recursive denoising of image blocks

Abstract

The invention discloses an image block adaptive recursive noise reduction method, which divides the noise reduction results of the current image and the previous frame image into multiple sub-blocks, performs motion detection on each sub-block, and obtains the motion parameters of each sub-block; Combine adjacent sub-blocks that belong to the same motion block into a motion area; calculate the noise reduction coefficient k of the front and rear frames through the image acquisition frequency parameter, the distance parameter between the sub-block and the motion area, and the motion parameter m; according to the calculated noise reduction coefficient and the recursive denoising formula to obtain the denoising result of the nth frame image x(n). The invention also discloses an image block adaptive recursive noise reduction device. The present invention adaptively adjusts the noise reduction parameters according to the noise level of each block, motion conditions, frame frequency, and the distance between the current block and the moving area, effectively eliminating motion drag without weakening the noise reduction effect in the static area. tail phenomenon and can reduce noise differences between blocks.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an image block adaptive recursive noise reduction method and device. Background technique [0002] Image denoising, especially sequence images in medical images, generally adopts recursive filtering method. However, the simple recursive filtering process cannot take into account the elimination of noise and motion artifacts of moving images. For still image sequences, when the recursion coefficient is large, the recursion effect is better; but for moving image sequences, the content described by each frame image has a "misalignment" in the spatial position, and recursive noise reduction will cause image motion artifacts. [0003] In order to reduce motion artifacts, it is necessary to change the recursion coefficient according to the motion of the image. The greater the relative motion between two source images, the smaller the corresponding coefficient should be. Whe...

AI Technical Summary

Problems solved by technology

First, motion detection is performed on the entire image, and when motion is detected, the overall noise reduction level is reduced. This method often fails to achieve the ideal denoising effect: when motion occurs, the noise reduction level of the entire image is reduced, so that the entire image cannot reach the desired level. To achieve a better noise reduction effect, different noise reduction parameters or noise reduction methods are used between the motion frame and the still frame, so that the noise level between the two frames of images is different, so there will be obvious noise differences

However, the method of dividing the image into blocks and using different noise reduction parameters for moving blocks and static blocks will have obvious noise differences between blocks.

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