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Low-illumination image enhancement and denoising method based on dual complementary prior constraints

An image enhancement and low-illumination technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as noise amplification, and achieve the effect of solving noise amplification

Active Publication Date: 2022-08-05
XIAN UNIV OF TECH
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Problems solved by technology

[0004] The purpose of the present invention is to provide a low-illuminance image enhancement and denoising method based on double complementary prior constraints, which solves the problem of noise amplification in low-illuminance image enhancement technology

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  • Low-illumination image enhancement and denoising method based on dual complementary prior constraints
  • Low-illumination image enhancement and denoising method based on dual complementary prior constraints
  • Low-illumination image enhancement and denoising method based on dual complementary prior constraints

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Embodiment Construction

[0067] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0068] Step 1, obtain the low-illumination image I that needs to be enhanced through image acquisition equipment low ,like figure 1 As shown in the middle image a, the illumination is low and blurry. And perform Retinex decomposition, the resulting illumination components and reflection components are as follows figure 1 shown in b and c.

[0069] Step 2, the low-light image I obtained in step 1 low Decomposed into illumination component L and reflection component R noise , when solving L, two points need to be considered: one is that L should have the same value as I low Similar texture features; the second is that there is no noise in L, which makes the low-light image I low The noise in are manifested in R noise in, as figure 2 shown in a.

[0070] Step 2 is as follows:

[0071] The low-light image I acquired in step 1 above low ...

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Abstract

The invention discloses a low-illumination image enhancement and denoising method based on dual complementary prior constraints, and the method comprises the following steps: solving an illumination component, and guaranteeing that the illumination component does not contain noise and all the noise is contained in a reflection component; on the basis of the non-local self-similarity principle, noise is constructed for the reflection component to remove internal prior constraints; on the basis of a large number of natural images, noise is constructed for the enhanced images, and external prior constraints are removed; and combining the built internal and external prior constraints, enabling the two prior constraints to be dynamically complementary, and solving a final enhancement result. By adopting the method, the problem of noise amplification in a low-illumination image enhancement technology is solved.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, in particular to a low-illumination image enhancement and denoising method based on double complementary prior constraints. Background technique [0002] Under conditions such as night or backlight, the collected images often have large dark areas, low contrast, little effective information, and serious noise pollution. These degradations bring great challenges to subsequent visual tasks. Low-light image enhancement aims to restore the real information of the scene as much as possible through some principles and methods. Early research is mainly oriented to encoded image formats (such as PNG, JPEG and BMP, etc.). In recent years, with the improvement of the computing power of image acquisition devices, there are more and more enhancement methods for raw optical sensor data (Raw format). However, many portable capture devices still do not support data in Raw format, and in some ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20081G06T5/70Y02T10/40
Inventor 都双丽赵明华刘怡光徐振宇尤珍臻
Owner XIAN UNIV OF TECH
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