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Low-brightness vehicle bottom image enhancement method and device and storage medium

An image enhancement and low-brightness technology, applied in the field of image processing, can solve problems such as difficult to apply 4k-level pixel images, large amount of calculation, and processing effect depends on the training data set, etc., to achieve excellent brightness enhancement effect, improve operating efficiency, and excellent Effect of Brightness Enhancement Results

Active Publication Date: 2021-06-22
南京索安电子有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although high image visual quality can be obtained, the processing effect of this method depends largely on the quality of the training data set
And the amount of calculation is too large, it is difficult to apply to images with 4k pixels

Method used

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  • Low-brightness vehicle bottom image enhancement method and device and storage medium
  • Low-brightness vehicle bottom image enhancement method and device and storage medium
  • Low-brightness vehicle bottom image enhancement method and device and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] With reference to the method flow process of the present invention (as figure 2 ), the specific method includes the following steps:

[0054] step 1. Input a low-brightness image: read as figure 1 For the low-brightness car bottom image shown, the input image is read in RGB format, saved to the variable imgInput, and the optimal parameters are calculated according to the input low-brightness image imgInput, and a high-brightness image imgHighlight is generated.

[0055] Step 1 is as follows:

[0056] Step 1-1, for the input low-brightness image imgInput, call the cvtColor function of opencv to calculate the pixel values ​​of the H, L, and S channels corresponding to the input image, merge and save them into a new variable imghls, and obtain its brightness channel L.

[0057] Step 1-2, determine the value range of parameters BS and CL, and the search granularity. Among them, BS and CL respectively refer to the hyperparameters tileGridSize and clipLimit that need to ...

Embodiment 2

[0089] The present invention also provides a low-brightness vehicle bottom image enhancement device, including a processor and a memory; programs or instructions are stored in the memory, and the programs or instructions are loaded and executed by the processor to realize the low-brightness embodiment 1 Image enhancement method for vehicle underbody.

Embodiment 3

[0091]The present invention also provides a computer-readable storage medium. The computer-readable storage medium may be a non-volatile computer-readable storage medium. The computer-readable storage medium may also be a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium, and when the instructions are run on the computer, the computer is made to execute the low-brightness under-vehicle image enhancement method of Embodiment 1.

[0092] Those skilled in the art can clearly understand that the essence of the technical solution of the present invention or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of software products, and the computer software products Stored in a storage medium, including several instructions to enable a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods d...

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Abstract

The invention discloses a low-brightness vehicle bottom image enhancement method and device based on exposure fusion and a storage medium. The method comprises the following steps: converting an input image into an HLS color space, and obtaining an H channel, an L channel and an S channel; for a brightness channel L, firstly performing self-adaptive search of super-parameters tileGridSize and clipLimit required by local histogram equalization, and then performing local histogram equalization on the brightness channel by using the obtained parameters to obtain a high-brightness image; and carrying out Poisson editing-based exposure fusion on the high-brightness image obtained in the previous step and the original low-brightness image, then carrying out bilateral filtering, and finally obtaining an image after brightness enhancement. According to the invention, the calculation complexity of an algorithm is effectively reduced, meanwhile, excellent details and truth are guaranteed, and experiments verify that the method achieves excellent brightness enhancement effects and efficiency on a 4K-level pixel image.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a low-brightness image enhancement method based on exposure fusion. Background technique [0002] In the process of large-scale application of computer vision algorithms, the low quality of the input image is a major difficulty in the implementation of the algorithm. For example, in the application scenario of foreign object detection under the car, the low The brightness enhancement of the image can greatly improve the application effect of the subsequent visual algorithm. [0003] In the field of computer vision and image processing, the current mainstream low-brightness image enhancement methods can be mainly classified into: low-brightness image enhancement methods based on grayscale transformation, methods based on Retinex theory, and low-brightness image enhancement methods based on deep learning. [0004] The low-brightness image enhancement method based on grays...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T3/40
CPCG06T3/4007G06T2207/20221G06T2207/10024G06T5/92
Inventor 路通杨国强赵智玉徐梅娟
Owner 南京索安电子有限公司