Vehicle-mounted high-quality imaging method based on two-step recovery

An imaging method and high-quality technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as inability to quickly and accurately find targets, unclear videos or images, etc., and achieve high-quality image restoration and good application prospects Effect

Inactive Publication Date: 2017-03-08
CHONGQING UNIV
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Problems solved by technology

Existing self-driving cars often suffer from inability to spot targets quickly and accur...

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  • Vehicle-mounted high-quality imaging method based on two-step recovery
  • Vehicle-mounted high-quality imaging method based on two-step recovery
  • Vehicle-mounted high-quality imaging method based on two-step recovery

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Embodiment Construction

[0021] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] figure 1 It is a flowchart of the method of the present invention, as shown in the figure, the vehicle-mounted high-quality imaging method based on two-step restoration provided by the present invention includes the following steps:

[0023] S1: In the imaging process of the vehicle environment, the degradation process of the vehicle image caused by the Gaussian blur of the optical imaging system and the motion blur caused by relative motion is expressed as:

[0024]

[0025] Among them, f(x,y) is the original clear image, h 1 (x, y) is the inherent point spread function of the vehicle environment imaging system, h 2 (x, y) is the moving point spread function in the vehicle environment, n(x, y) is the additive noise, and g(x, y) is the degraded image;

[0026] S2: Estimate the moving point spread function h of g(x, y) using the...

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Abstract

The invention relates to a vehicle-mounted high-quality imaging method based on two-step recovery. The method comprises following steps of: S1: expressing the degenerative process of a vehicle-mounted image as the formula shown in the description, wherein f (x, y) is the original clear image, h1 (x, y) is the fixed point spread function of a vehicle-mounted environment imaging system, h2 (x, y) is a motion point spread function under the vehicle-mounted environment, n (x, y) is the additive noise, and g (x, y) is the degenerative image; S2: using a "cepstrum method" to estimate the motion point spread function h2 (x, y) of the g (x, y), and using ultra Lapras regularization ultra resolution algorithm to recover a moving fuzzy image so as to obtain g1 (x, y); and S3: through a "knife edge method", measuring the point spread function h1 (x, y) of a vehicle-mounted optical imaging system, using an improved L-R algorithm to recover the g1 (x, y) fuzzy image and finally recovering a quite clear image f1 (x, y). According to the invention, the image is recovered through two steps, so disadvantages in current methods can be well overcome and high-quality image recovery is achieved.

Description

technical field [0001] The invention belongs to the technical field of high-quality rapid imaging in a vehicle environment, and relates to a two-step restoration-based high-quality vehicle imaging method. Background technique [0002] Driverless cars often have to track objects on the road based on on-board video to control their own behavior. A frequent problem with existing driverless cars is that they cannot spot objects quickly and accurately. Videos or images obtained by existing vehicle-mounted imaging devices are usually not clear. This "unclearness" is caused by many reasons, but the Gaussian blur caused by the optical imaging system and the motion blur caused by relative motion during the imaging process in the vehicle environment are the main reasons. In order to improve video quality, the influence of these two factors must be minimized. Using restoration methods to improve in-vehicle video and image quality is an important approach that has received extensive ...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/003G06T2207/20201G06T2207/30252
Inventor 刘丹平刘松许亮吕皖何小敏秦天天于娟娟舒英王雪菡马玉霖古文邹熙肴
Owner CHONGQING UNIV
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