Edge Recognition of Color Image Based on Super-Resolution Imaging Technology
The traditional edge recognition technology for color images is limited by the resolution constraints, resulting in blurred edges, and broken and uneven lines. Therefore, in this paper, a super-resolution imaging technology is used to overcome the resolution of traditional methods, and obtain sharper edges in color images. In order to better define the distinct colors in an image, edge recognition technology uses the double histogram color image for equalization processing. According to the changes in gray value, the corner feature of the image is extracted, and the edge model is constructed by a double interpolation algorithm to obtain the basic contour of the image. Finally, the contour features of the color image are identified by superresolution imaging technology, and the edge recognition process is completed. The experiment is divided into two stages, and the selected test objects differ in terms of color, structure and content. After two rounds of testing, we can see that by applying the edge recognition technology proposed in this study, the edge of the color image is continuous and smooth; while the image edge obtained by three traditional technologies are not smooth; rather, it contains a large number of broken lines. The entropy of image information was used to evaluate the processed image, and it was found that the edge recognition technology applied in this study is capable of better edge detection.
Keywords: Super-resolution Imaging Technology, Color Image, Edge Recognition
S. Ren, Y. Zhang, "Edge Recognition of Color Image Based on Super-Resolution Imaging Technology", Engineering Intelligent Systems,
vol. 30 no. 3, pp. 217-226, 2022.