An image adaptive enhancement method, device and image processing equipment

Abstract

The invention is applicable to the field of image and video processing, and provides an image self-adaptive enhancement method, device and image processing equipment. The method includes: extracting a brightness component of an input image; counting local brightness features and local grayscale contrast features of the image according to the brightness component of the image; generating a global contrast enhancement factor and brightness according to the local brightness features and local grayscale contrast features of the image Mapping curve; adjust the contrast of the image according to the local variance information of the image and the global contrast enhancement factor; adjust the brightness of the contrast-enhanced image according to the brightness mapping curve, and stretch the brightness of the low-illuminance area; output the image. The invention can obtain natural and clear image results, especially can significantly improve the visual effect of the low-illuminance area of ​​the image, and maintain the naturalness of the high-illuminance area, and can be widely used in the related fields of image and video processing.

Description

technical field

[0001] The invention belongs to the field of image and video processing, and in particular relates to an image self-adaptive enhancement method, device and image processing equipment. Background technique

[0002] Video images obtained by cameras and monitoring systems have become an important source of information for people to obtain. Whether high-quality video images can be obtained is of great significance for people to quickly and accurately analyze the useful information contained in the images. However, during the image acquisition process, it is affected by various factors such as weather, light, and equipment, resulting in problems such as uneven illumination, insufficient brightness, and loss of details in the overall image. This not only affects the visual effect of the image, but also greatly reduces the reliability of its subsequent processing and analysis.

[0003] Contrast enhancement can improve the overall or local contrast of the image to i...

Examples

Embodiment 1

[0037] see figure 1 , the image adaptive enhancement method provided by Embodiment 1 of the present invention includes the following steps: It should be noted that if there are substantially the same results, the image adaptive enhancement method of the present invention does not use figure 1 The flow sequence shown is limited.

[0038] S101. Extract a brightness component of an input image.

[0039] In Embodiment 1 of the present invention, the input image may be a grayscale image or a color image.

[0040] If the input image is a grayscale image, S101 may specifically be: extracting a brightness component of the image from the input grayscale image.

[0041] If the input image is a YCbCr color image, S101 may specifically be: extracting a luminance component Y in the input YCbCr color image.

[0042] If the input and image are RGB color images, then S101 can specifically be: according to the formula Execute the processing of RGB input pixel to YCbCr color space conversi...

Embodiment 2

[0078] see Figure 8 , the image adaptive enhancement device provided by Embodiment 2 of the present invention includes:

[0079] Extraction module 11, for extracting the luminance component of the input image;

[0080] Statistical module 12, is used for according to the local brightness feature of image and the local grayscale contrast characteristic of statistical image according to the brightness component of image;

[0081] Generating module 13, is used for generating global contrast enhancement factor and brightness mapping curve according to local brightness feature and local grayscale contrast feature of image;

[0082] The contrast adjustment module 14 is used to adjust the contrast of the image according to the local variance information of the image and the global contrast enhancement factor;

[0083] The brightness adjustment module 15 is used to adjust the brightness of the contrast-enhanced image according to the brightness mapping curve, and stretch the brightn...

Embodiment 3

[0087] Embodiment 3 of the present invention provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the image adaptive enhancement method provided in Embodiment 1 of the present invention is implemented. A step of.

technical field

[0001] The invention belongs to the field of image and video processing, and in particular relates to an image self-adaptive enhancement method, device and image processing equipment. Background technique

[0002] Video images obtained by cameras and monitoring systems have become an important source of information for people to obtain. Whether high-quality video images can be obtained is of great significance for people to quickly and accurately analyze the useful information contained in the images. However, during the image acquisition process, it is affected by various factors such as weather, light, and equipment, resulting in problems such as uneven illumination, insufficient brightness, and loss of details in the overall image. This not only affects the visual effect of the image, but also greatly reduces the reliability of its subsequent processing and analysis.

[0003] Contrast enhancement can improve the overall or local contrast of the image to i...

Examples

Embodiment 1

[0037] see figure 1 , the image adaptive enhancement method provided by Embodiment 1 of the present invention includes the following steps: It should be noted that if there are substantially the same results, the image adaptive enhancement method of the present invention does not use figure 1 The flow sequence shown is limited.

[0038] S101. Extract a brightness component of an input image.

[0039] In Embodiment 1 of the present invention, the input image may be a grayscale image or a color image.

[0040] If the input image is a grayscale image, S101 may specifically be: extracting a brightness component of the image from the input grayscale image.

[0041] If the input image is a YCbCr color image, S101 may specifically be: extracting a luminance component Y in the input YCbCr color image.

[0042] If the input and image are RGB color images, then S101 can specifically be: according to the formula Execute the processing of RGB input pixel to YCbCr color space conversi...

Embodiment 2

[0078] see Figure 8 , the image adaptive enhancement device provided by Embodiment 2 of the present invention includes:

[0079] Extraction module 11, for extracting the luminance component of the input image;

[0080] Statistical module 12, is used for according to the local brightness feature of image and the local grayscale contrast characteristic of statistical image according to the brightness component of image;

[0081] Generating module 13, is used for generating global contrast enhancement factor and brightness mapping curve according to local brightness feature and local grayscale contrast feature of image;

[0082] The contrast adjustment module 14 is used to adjust the contrast of the image according to the local variance information of the image and the global contrast enhancement factor;

[0083] The brightness adjustment module 15 is used to adjust the brightness of the contrast-enhanced image according to the brightness mapping curve, and stretch the brightn...

Embodiment 3

[0087] Embodiment 3 of the present invention provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the image adaptive enhancement method provided in Embodiment 1 of the present invention is implemented. A step of.

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