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Image brightness adjusting method and device, electronic equipment and storage medium

A technology of image brightness and adjustment method, applied in the computer field, can solve the problems of reducing contrast, unable to maintain image fidelity, poor effect, etc., and achieve the effect of reasonable brightness distribution

Pending Publication Date: 2020-10-02
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Contrast-based enhancement methods mainly include histogram-based, filter-based, and transformation-based approaches; for example, histogram matching between red and green channels is used as a preprocessing step for vessel segmentation, which can Contrast of overall dark features such as MA, but reduces the contrast of bright objects with tiny dark objects such as microangiomas (MAs); augmentation with a matched filter can improve local contrast and help vessel segmentation, but not Maintains image fidelity, it also affects other structures present in the image; contourlet-based enhancements are less effective in areas of poor fundus contrast

Method used

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  • Image brightness adjusting method and device, electronic equipment and storage medium
  • Image brightness adjusting method and device, electronic equipment and storage medium
  • Image brightness adjusting method and device, electronic equipment and storage medium

Examples

Experimental program
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Effect test

Embodiment 1

[0040] figure 1 This is a schematic flowchart of the image brightness adjustment method provided in the first embodiment of the present application. The method can be performed by an image brightness adjustment device or electronic device, and the device or electronic device can be implemented by software and / or hardware. Or the electronic device can be integrated in any smart device with network communication function. like figure 1 As shown, the method for adjusting image brightness may include the following steps:

[0041] S101. Acquire an observation image, wherein the observation image is an image in a red, green, and blue color space.

[0042] In a specific embodiment of the present application, the electronic device may acquire an observation image, wherein the observation image is an image in a red, green, and blue color space (ie, an RGB space). The RGB space is based on the three basic colors of red (Red), green (Green), and blue (Blue), which are superimposed to ...

Embodiment 2

[0053] image 3 This is a schematic flowchart of the image brightness adjustment method provided in the second embodiment of the present application. like image 3 As shown, the method for adjusting image brightness may include the following steps:

[0054] S301. Acquire an observation image, wherein the observation image is an image in a red, green, and blue color space.

[0055] S302. Separate the green channel image corresponding to the observation image from the observation image.

[0056] In the specific embodiment of the present application, the electronic device may separate the G channel image corresponding to the observation image from the observation image. Because the G channel image retains a lot of contrast information, the background image extraction operation is performed on the G channel, and the pixel points of the background image are extracted from the observed image using the mean and standard deviation of the sampling points.

[0057] S303. Calculate t...

Embodiment 3

[0066] Figure 5 This is a schematic flowchart of the method for adjusting the brightness of an image provided in Embodiment 3 of the present application. like Figure 5 As shown, the method for adjusting image brightness may include the following steps:

[0067] S501. Acquire an observation image, wherein the observation image is an image in a red, green, and blue color space.

[0068] S502. Separate the green channel image corresponding to the observation image from the observation image.

[0069] S503. Calculate the mean and standard deviation of each pixel in the green channel image; wherein, the pixels in the green channel image include sampling points and non-sampling points.

[0070] S504. According to the mean value and standard deviation of each pixel point in the green channel image and the pixel value of each pixel point, separate a background image corresponding to the green channel image from the green channel image.

[0071] In the process of image acquisitio...

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Abstract

The invention discloses an image brightness adjustment method and device, electronic equipment and a storage medium, relates to the fields of artificial intelligence, deep learning and image processing, and can be specifically applied to fundus image screening. According to the invention, the specific scheme is that the method comprises the steps: acquiring an observation image, wherein the observation image is an image of a red, green and blue color space; separating a background image corresponding to the observation image from the observation image; determining a display parameter value corresponding to the observation image according to the background image; and adjusting the brightness of the observation image according to the display parameter value corresponding to the observation image. According to the embodiment of the invention, the proper display parameter value can be intelligently selected according to the brightness distribution of the observation image, so the brightness distribution of the observation image is more reasonable.

Description

technical field [0001] The present application relates to the field of computer technology, and further relates to the fields of artificial intelligence, deep learning and image processing, in particular to an image adjustment method, apparatus, electronic device and storage medium. Background technique [0002] Fundus image adaptive brightness adjustment technology (Fundus image adaptive brightness adjustment) refers to automatic adjustment according to the brightness distribution of the fundus image itself, so that the image quality conforms to the unified specification. In the actual business scenario, due to factors such as differences in the model of image acquisition equipment, insufficient lighting, too small dynamic range of the imaging sensor, and the level of technicians taking pictures, the fundus images obtained by the image acquisition equipment have uneven brightness distribution and poor quality. There is a gap between the fundus image of the algorithm model a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20008G06T2207/30041G06T5/92
Inventor 黄甜甜尚方信杨大陆杨叶辉王磊许言午
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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