Low-light and low-altitude remote sensing image enhancement method based on retinex theory

Abstract

The invention relates to a Retinex-theory-based low-illumination low-altitude remote sensing image enhancing method, mainly comprising the following steps of: transforming a low-illumination low-altitude remote sensing image from a red, green, blue (RGB) color space into a hue, saturation, intensity (HSI) color space; adjusting a luminance component I and a saturation component S on the premise of guaranteeing that a hue component H is not changed, so that the processed image accords with visual characteristics of eyes of a human body and a color distortion phenomenon is avoided; transforming the enhanced image from the HIS color space into the RGB color space; and performing convolution operation by using a laplace operator and an original image to obtain an edge image; and superposing the enhanced image and the edge image to obtain the finally enhanced image. By virtue of the method, the luminance and the contrast of the low-illumination low-altitude remote sensing image are improved, the color distortion phenomenon is avoided, and the low-illumination low-altitude remote sensing image has rich edge information and accords with the visual characteristics of the eyes of the human body.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and relates to a low-illuminance and low-altitude remote sensing image enhancement method based on the Retinex theory. Background technique [0002] Low-altitude remote sensing images contain very rich information, but due to the influence of external factors such as sensor performance, bad weather, and uneven illumination, the acquired remote sensing images often have problems such as uneven brightness, low contrast, color distortion, and blurred edges. It leads to the deterioration of image quality and affects the subsequent interpretation and information extraction of remote sensing images. Therefore, in order to improve image quality and extract more usable information, fast and efficient image enhancement algorithms have become one of the key contents to promote the development of image analysis and understanding fields. [0003] Low-light and low-altitude remote sen...

AI Technical Summary

Problems solved by technology

This type of method can compress the dynamic range of the image and improve the contrast of the image, but the brightness information and the color information are mixed and processed in accordance with the human visual characteristics, resulting in different degrees of color distortion in the enhanced image.

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