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An image and image pair technology, applied in the field of image processing, can solve the problems of low real-time performance, increased algorithm complexity, and long operation time, and achieves the effect of high real-time performance, fast construction and processing speed, and simplified operation.
Active Publication Date: 2018-10-12
SOUTH CHINA NORMAL UNIVERSITY
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However, this method needs to continuously introduce new target features to increase the discrimination of dictionary classification, which increases the complexity of the algorithm, takes a long time to calculate, and has low real-time performance.
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Embodiment 1
[0039] see figure 1 , which is a flow chart of the image rain removal method in Embodiment 1 of the present invention. The image deraining method comprises the following steps:
[0040] Step S1: Construct an image training database; wherein, the image training database includes multiple pairs of no rain-rain-pure rain pattern image pairs.
[0041] see figure 2 , which is a flow chart of constructing an image training database in Embodiment 1 of the present invention.
[0042] Described construction image training database comprises the steps:
[0043] Step S11: Obtain multiple no-rain images and multiple pure rain pattern images;
[0044] Step S12: through the linear static rain pattern superposition model, add the pure rain pattern image to the rain-free image to obtain the corresponding linear rain image;
[0045] Step S13: through the non-linear static rain pattern mixture model, add the pure rain pattern image to the non-rain image to obtain the corresponding nonline...
Embodiment 2
[0103] The present invention also provides an image deraining system, including a processor, adapted to implement instructions; and a storage device, adapted to store a plurality of instructions, and the instructions are adapted to be loaded and executed by the processor:
[0104] Construct image training database; Wherein, comprise many pairs of no rain-rain-pure rain pattern image pairs in the image training database;
[0105] According to the no-rain-rain-pure rain pattern image pairs in the image training database, a twin convolutional network structure for rain removal is constructed;
[0106] Filtering the image to be rained to obtain high-frequency information and low-frequency information of the image to be rained;
[0107] Input the high-frequency information of the image to be rained into the twin convolutional network structure for rain removal to obtain the high-frequency information of the corresponding no-rain image; then add the high-frequency information of the...
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Abstract
The invention relates to an image rain removal method and system. The method comprises the steps: S1, constructing an image training database, wherein the image training database comprises a pluralityof no rain-rain-only rain grain image pairs; S2, according to the no rain-rain-only rain grain image pairs in the image training database, constructing a twin convolution network structure for rain removal; S3, performing filtering on an image to be subjected to rain removal to obtain high frequency information and low frequency information of the image to be subjected to rain removal; and S4, inputting the high frequency information of the image to be subjected to rain removal into the twin convolution network structure for rain removal to obtain a high frequency information of a corresponding no-rain image, and adding the low frequency information of a rain image into the obtained high frequency information of a no-rain image to obtain the corresponding no-rain image. According to the method, the twin convolution network structure is constructed by the no rain-rain-only rain grain image pairs, operation is simplified, the construction processing speed is high, the instantaneity is good, and the clear no-rain image can be obtained by constructing the twin convolution network structure with high robustness.
Description
technical field [0001] The invention relates to the field of image processing, in particular to a method and system for removing rain from an image. Background technique [0002] With the rapid development of modern information technology, people hope to obtain clearer images, and for this purpose, it is usually necessary to remove the rain streaks in the image. [0003] The traditional image deraining method mainly adopts the method based on sparse dictionary learning. The core of this method is to learn a target rain pattern sparse dictionary from the synthesized rain pattern library, and distinguish the rain pattern from the background through the target rain pattern sparse dictionary. image. However, this method needs to continuously introduce new target features to increase the discrimination of dictionary classification, which increases the complexity of the algorithm, takes a long time to calculate, and has low real-time performance. Contents of the invention [0...
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