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

A multi-scale feature and frame image technology, which is applied in the field of image processing, can solve problems such as rainwater cannot be detected at high frequency, data has not been collected, and rainwater is missed.

Active Publication Date: 2019-02-19
SHANGHAI JIAO TONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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 processi...

Method used

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

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Experimental program
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Embodiment

[0057] Step 1: Establish a database for training the entire deraining model.

[0058] The database includes two parts: training set and test set. The training set contains rainy images and their corresponding non-rainy images. In this embodiment, the training set includes 700 pictures, 500 of which are selected from the first 800 pictures in the UCID image database, and the remaining 200 are from the training set in the BSD-500 database. Among them, the rainy image is synthesized by artificially adding rain lines, and the shape, intensity and direction of the rain lines are diverse to ensure the generalization ability. The test set is divided into two categories: the synthetic picture test set and the natural picture test set; the synthetic picture test set contains the original image without rain, so the peak signal-to-noise ratio (PSNR) on the luminance channel (luminance channel) can be calculated at last Equal quantitative indicators to evaluate the image quality (the br...

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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...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06N3/04G06N3/08
CPCG06N3/084G06T5/003G06N3/048
Inventor 徐奕张峥倪冰冰杨小康
Owner SHANGHAI JIAO TONG UNIV
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