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

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 ...

AI Technical Summary

Problems solved by technology

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

The video or image obtained by the existing vehicle imaging equipment is usually not clear

Images