Bilateral adaptive image visualization enhancement method and imaging system

Abstract

A bilateral self-adaptive image visualization enhancement method comprises the following steps that an underwater gating image is collected for a target, and the brightness and the contrast ratio of the image are low; performing grey level histogram statistics on the original image; selecting a gray scale with a non-zero pixel number for the gray scale histogram to establish a new gray scale histogram set, performing multi-neighborhood median filtering, and removing noise influence; selecting a local maximum value for the non-zero gray histogram set, solving a mean value of the local maximum value, and determining the mean value as an upper limit value; solving a lower limit value by utilizing the upper limit value and the non-zero gray level set; correcting the gray histogram by using theupper limit value and the lower limit value to obtain a corrected gray histogram; performing gray level accumulation statistics by utilizing the corrected gray level histogram, and establishing an accumulation histogram; and establishing a gray scale conversion equation, and performing gray scale conversion on the original image pixel by pixel to obtain an enhanced image. According to the method,the image enhancement of the low-brightness and low-contrast image is realized, and the applicability is good.

Description

technical field [0001] The invention relates to the technical field of image enhancement, in particular to a bilateral self-adaptive image visualization enhancement method and an imaging system. Background technique [0002] Image enhancement is a technique to improve image contrast and brightness, which can be widely used in underwater imaging, nighttime imaging and infrared imaging and other fields. The histogram enhancement in image enhancement is to use the image histogram to establish the grayscale conversion equation, and the enhanced image is obtained through the grayscale conversion of the original image, which has the characteristics of small amount of calculation and good real-time performance. However, the traditional histogram enhancement method will lead to over-enhancement of the image, resulting in oversaturation, loss of image details, and local overbrightness of the image, which is not conducive to visual observation. The grayscale image obtained by range-g...

AI Technical Summary

Problems solved by technology

However, the traditional histogram enhancement method will lead to over-enhancement of the image, resulting in oversaturation, loss of image details, and local overbrightness of the image, which is not conducive to visual observation

The grayscale image obtained by range-gated laser imaging has the characteristics of low contrast and low brightness. The grayscale distribution of image pixels is mainly concentrated at low values, and the target information cannot be effectively identified.

The contrast and brightness of the original image of the gated image are too low, so that the target information is submerged in the background information and cannot be effectively distinguished. Using traditional histogram enhancement for image enhancement, the image contrast and brightness can be effectively enhanced, but oversaturation will occur Phenomenon, the gray value of the target area reaches the maximum value, and the local detail information is lost

Therefore, for low-contrast and low-brightness gated images, the traditional histogram enhancement method cannot effectively enhance target details

Images