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Edge information-based multi-scale blurred image blind restoration method

A technology for blurring images and edge information, applied in image enhancement, image data processing, instruments, etc., can solve problems such as difficult convergence, convergence failure, true value deviation, etc., to achieve the effect of strong noise suppression ability and low computational complexity

Inactive Publication Date: 2010-12-29
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

However, due to the ill-conditioned nature of the problem itself and the lack of information, it is often difficult to converge or fail to converge when solving. At this time, both the fuzzy kernel and the restoration map will deviate greatly from the real value

Method used

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  • Edge information-based multi-scale blurred image blind restoration method
  • Edge information-based multi-scale blurred image blind restoration method
  • Edge information-based multi-scale blurred image blind restoration method

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Embodiment Construction

[0122] The input information of the inventive method is the fuzzy image obtained by the shooting of a single piece to be processed. This figure adopts the Canon EOS 40D camera to shoot and obtain. Hand-held shooting in optical or digital anti-shake mode, use software to intercept the part to be processed for the blurred photos obtained image 3 , image 3 The medium blurred image has a width of 651 pixels and a height of 715 pixels. For images with more noise, denoising processing is required.

[0123] Before restoring the image for the last time, image processing of each scale is performed on a single-channel image, such as converting a color three-channel image to a single-channel grayscale mode for processing. Then use the method of gradually expanding each scale of the tower pyramid to deal with it, and set a moderate ratio for the scaling between each two adjacent scales The bilinear difference method is used for scaling. For general pictures with a width of about 500...

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Abstract

The invention discloses an edge information-based multi-scale blurred image blind restoration method, which comprises the following steps of: circularly and gradually restoring an image from a small scale layer to a large scale layer, setting self-adaptive parameters at different scales, and processing each scale layer, namely bilaterally filtering the restored image to obtain an image of which the noise and ripple are removed; performing shock wave filtering to obtain an image with high-strength contrast edges; solving the edges, and combining a fuzzy core initial value and a fuzzy graph to obtain an accurate fuzzy core; restoring a fuzzy image at the current scale to obtain a clear restored image by using the solved fuzzy core; sampling and amplifying in the current scale layer to obtain the restored image and a fuzzy core initial value of an adjacent large scale layer, and performing cycle operation on the adjacent large scale layer. The edge information-based multi-scale blurred image blind restoration method can effectively converge various images in different fuzzy degrees, and compared with a general blind restoration method which directly solves the energy minimization, the blurred image blind restoration method has the advantages of low computational complexity and high noise suppression capacity.

Description

technical field [0001] The invention relates to the technical field of image blind restoration, in particular to a robust multi-scale fuzzy image restoration method based on edge information. Background technique [0002] When shooting an object with a camera, there may be relative movement or shaking between the camera and the object during the exposure process, so the obtained image will appear blurred. For example, the forward propulsion of the aircraft and the vibration of the loading platform during the aerial photography of the ground, the shaking of the ordinary digital camera when the object is held in hand and the door is released and opened, etc., many shooting environments will cause motion blur. Under certain image acquisition conditions, how to use the obtained information to obtain a clearer image has become a particularly important step in the imaging process, and it is also a hot spot in the field of modern image processing. It is used in astronomical photogr...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 戴朝约冯华君徐之海李奇
Owner ZHEJIANG UNIV
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