Abstract
Road edge detection from remote sensing images, as an important ground object type, plays an important role in people’s life and travel and urban planning and development, and extracting road information from remote sensing images has practical scientific value and practical significance. However, with the development of remote sensing technology, while the resolution of remote sensing images is improved, the information describing ground objects becomes more and more abundant, and the difficulty of identifying and extracting road information is also increased. In the process of acquiring remote sensing images, the actual system is subjected to various kinds of noise interference. Different environmental interference and system defects will introduce noises with completely different distribution and statistical characteristics to remote sensing images. Aiming at the problem that the detection effect of traditional algorithms becomes worse due to the influence of noise on remote sensing images, a wavelet transform denoising method and morphological gradient operator are proposed. By selecting appropriate structural elements of remote sensing images, noise pixels cannot participate in morphological calculation, and the noise intensity changes with the size of quantum superposition state structural elements. Therefore, a morphological gradient operator is established and applied to edge detection of remote sensing images. Finally, the experimental results show that the method proposed in this article is better than other directions in terms of effect through road edge detection and matching. This method can effectively reduce noise. Compared with other algorithms, the method proposed in this article has certain advantages.
Highlights
Remote sensing technology is a kind of detection technology that arose in the 1960s
The noise of the original image is processed by wavelet, and the image with reduced noise is more effective for the later edge detection
The 3 × 3 median filtering Sobel operator, Roberts’s operator, Prewitt operator and wavelet and morphological gradient operator method proposed in this article are used to detect the edge of Lena image
Summary
Remote sensing technology is a kind of detection technology that arose in the 1960s. Based on the characteristics of electromagnetic waves radiated by long-range targets, A variety of cutting-edge sensing instruments are used for acquisition, And the collected information is processed and imaged through certain technical conversion, a technical means for analyzing, identifying and comprehensively applying various ground object information benefits from the rapid development of remote sensing technology [1]. Guobin et al.: Road Identification Algorithm for Remote Sensing Images traditional road information collection methods, Road information detection method based on remote sensing image, the cost is lower; the wide coverage makes up for the disadvantages of traditional collection methods, the road information with good real-time and high accuracy can be obtained [2] On this basis, through the acquisition of road information and the mining of later data, it plays an important role in urban regional planning, traffic information management, vehicle travel guidance and vehicle navigation positioning. As an important source of road information, Real-time and accurate road information can be obtained through high-resolution remote sensing images This information provide data support for information collection of Intelligent Transportation System (ITS) and subsequent database construction, help to improve the operation efficiency of transportation system, and play an important role in urban development, social stability and people’s life. On the basis of analyzing the principles and applicable conditions of various road extraction methods, The methods are compared and improved, The general process of road extraction method can be summarized as follows: firstly, the road is roughly extracted to obtain the basic contour, and the corresponding method is adopted to trim and refine to obtain a purer road area
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