Dark channel and Gaussian combined prior art-based low-illuminance blind convolution image restoration method

Abstract

The invention discloses a dark channel and Gaussian combined prior art-based low-illuminance blind convolution image restoration method and belongs to the image restoration technical field. The method comprises the following steps that: a simple lens is utilized to shoot a blurred image under low illuminance; the restoration problem of the low-illuminance blurred image is transformed into the problem of blind convolution image restoration; dark channel prior art and Gaussian blurring kernel prior art are added to the objective function of a blind convolution image restoration algorithm; and a corresponding optimization algorithm is adopted for the objective function of the blind convolution image restoration algorithm, so that a restored clear image can be obtained. According to the method of the invention, the dark channel prior art and the Gaussian blurring kernel prior art are combined to solve the image restoration problem of the imaging of the simple lens under low illuminance; the dark channel prior art aims at a low-illuminance image, and the Gaussian blurring kernel prior art aims at an actual situation that the imaging blurring kernel of the simple lens is disk-shaped, and therefore, the dark channel prior art and the Gaussian blurring kernel prior art can be combined to well solve the restoration problem of a blurred image which is shot by the simple lens under low illuminance.

Description

technical field [0001] The invention relates to the field of digital image processing, in particular to the field of image restoration, in particular to a low-illuminance blind convolution image restoration method based on dark channel and Gaussian combination prior. Background technique [0002] At present, SLR cameras are playing an increasingly important role in people's daily lives. However, in order to compensate for the geometric distortion and aberration of the lens in the SLR lens and further improve the imaging quality, the design of the SLR lens is becoming more and more complex, even including dozens of independent optical devices. Complicated lenses will increase the volume and weight of the lens while improving the imaging quality, which will greatly increase the cost of the lens. In recent years, with the development of computational photography technology, simple lens combined with post-image restoration algorithm has gradually become a new research direction...

AI Technical Summary

Problems solved by technology

The main problem of this method is: according to the prior proposed by the image spectral information, if the original blurred image itself has rich spectral information, a good deblurring effect can be obtained.

However, if the spectrum of the original blurred image is mainly concentrated in certain frequency bands, or if the distribution of spectral information is uneven, a good deblurring effect cannot be obtained.

The spectral information of the fuzzy image obtained by shooting natural images with many edges under normal light is relatively rich, but in a low-light environment, the overall tone of the image captured by a simple lens is dark, and the image edges are more blurred due to the low-light environment. The spectral information of the illumination blurred image is mainly concentrated in the low frequency, and there is not much high frequency detail information, so this method cannot get a good deblurring effect

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