Single-frame rainfall removing method based on multi-scale feature fusion

Abstract

The invention provides a single frame image rain removing method based on multi-scale feature fusion, Feature extraction of rainless images with different scale receptive fields, then deconvolution operation to get the result of rainless images, using the combination of coarse-scale features and fine-scale features, to promote the rainless images generated by fine-scale to achieve the best effectof rainless. By removing rainlines on multiple scales, the algorithm can be used in a variety of rainwater situations, and the rainout algorithm is more universal. The invention cites the antagonisticerror and the perceptual error to construct a new error function, and trains the rain removing model without any prior knowledge, and does not need to preprocess and post-process the image, thus ensuring the integrity of the whole structure. The results on a plurality of test sets show that the invention can improve the peak signal-to-noise ratio on the luminance signal channel by 2-5dB.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular, to a single-frame image rain removal method based on multi-scale feature fusion, which is applied to processing a single-frame image with rain, so as to remove the rain in the image, restore the background image and restore the color of the original image. and detail to minimize distortion. Background technique [0002] In complex and changeable weather conditions, the pictures or videos taken by people are often disturbed or blurred by rain, snow, or fog, or the subject of the picture will be seriously disturbed. Rain, as one of the most common natural phenomena in life, will degrade human vision. In the case of rain, the distance rain line will have a reflection effect under the influence of light, and the quality of the captured pictures and videos will be seriously degraded. At the same time, the rain line will accumulate to form fog, and there will be rain an...

AI Technical Summary

Problems solved by technology

However, these traditional methods all have common problems: 1) The rainwater cannot be completely divided into high frequency in the decomposition of the image, and there will be residual rainwater components in the low frequency

2) The filter in the traditional image processing method cannot fully describe or detect all the forms of rain, which will lead to missed detection of rainwater

[0007] At present, there is no description or report of the similar technology of the present invention, and no similar data at home and abroad have been collected yet.

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