Image Denoising and Image Contour Detection
DOI:
https://doi.org/10.54097/wd660x73Keywords:
Image denoising, spatial domain methods, transform domain methods, image contour detection, Canny, Sobel detection, gaussian filtering, FPGA.Abstract
With the development of various fields in society, the demand for digital images has increased significantly. These digital images require image processing in many fields before they can be put into use, such as transportation, healthcare and remote sensing. After denoising and contour detection, digital images can play their role. So far, many image denoising and image contour detection methods have been proposed by researchers, each with different characteristics. In the aspect of image denoising, this paper reviews some image-denoising methods and FPGA implementations based on denoising filters provides the principles of these methods and discusses the advantages and disadvantages of these denoising methods and the advantages of FPGA implementations based on filters. In the aspect of image contour detection, traditional methods have prominent limitations when performing edge detection on complex scenes. This paper systematically reviews the improvement techniques of Canny and Sobel's classic edge detection methods, as well as the optimization of Gaussian filtering for detection performance, and explores their practicality in complex scenes.
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