Noise reduction method after histogram equalization of low-illumination image

An image histogram and low-illumination technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as cross-border, image blur, poor effect, etc., to improve the effect of noise reduction and reduce the risk of instability Effect

Active Publication Date: 2021-12-10
江苏稻源科技集团有限公司
View PDF5 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Although the histogram equalization algorithm is suitable for brightness enhancement of low-illumination pictures, and the Gaussian low-pass filter is suitable for noise reduction of ordinary pictures, the effect of Gaussian low-pass filter noise reduction on the image after the histogram equalization algorithm is not good. Because in the image after histogram equalization, low-brightness information is missing, high-brightness noise is amplified or crossed, and the image and noise are sparsely distributed and mixed together. At this time, using a Gaussian low-pass filter will cause image blur

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Noise reduction method after histogram equalization of low-illumination image
  • Noise reduction method after histogram equalization of low-illumination image
  • Noise reduction method after histogram equalization of low-illumination image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] The present invention will be further explained below in conjunction with the accompanying drawings.

[0031] The standard histogram equalization method includes the following steps:

[0032] 1. Traverse the entire image and count the number of pixels corresponding to each gray value;

[0033] 2. Calculate the probability of the number of pixels in each gray value PMF=corresponding number of pixels / total pixels;

[0034] 3. According to the gray value from small to large, calculate the cumulative probability CDF of each gray value = less than or equal to the sum of the probability of this gray value;

[0035] 4. Calculate the new gray value of each gray value after mapping = cumulative probability * maximum brightness * original gray value, and then round up.

[0036] Such as figure 1 Shown is the pixel brightness distribution of a typical low-light image at night, such as figure 2 It shows the brightness distribution of pixels after standard histogram equalization...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a noise reduction method after histogram equalization of a low-illumination image. The method takes a plurality of minimum brightness values as a reserved set and traverses all pixels, and comprises the following three situations of 1: for the pixel brightness values belonging to the reserved set, keeping the pixel brightness values unchanged; 2, for the pixel brightness values which do not belong to the reserved set, if the brightness values of eight pixels in a 5*5 area around the pixel belong to the reserved set, valuing the pixel brightness in the reserved set; and 3, for other situations, according to the pixel characteristics in the 5*5 area around the pixel, adaptively constructing a 5*5 filtering template, and calculating the brightness value of the pixel by using the filtering template. Compared with the noise reduction via a Gaussian low-pass filter, the method has the advantage that the information in a dark environment can be visually identified better.

Description

technical field [0001] The invention relates to a noise reduction method after histogram equalization of a low-illuminance image. Background technique [0002] Digital image acquisition is to use sensors such as cameras to convert optical signals into electrical signals and store, transmit and display them in digital form. Digital image processing is to optimize the collected digital images according to the purpose and scene of use. The common methods include: image Enhancement and restoration, image coding compression, image description, etc. [0003] Low-illumination images refer to images collected under low ambient light conditions. In order to be able to display clearly, it is necessary to enhance the brightness and reduce noise of the low-illumination images, so that the naked eye can obtain useful information in the images. The brightness enhancement of low-illumination images is playing an increasingly important role in practical applications. In the field of outdoo...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/40
CPCG06T5/002G06T5/40
Inventor 陈石王彬徐凯赵佳佳袁明亮王中杰
Owner 江苏稻源科技集团有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap