Design of Smart Edge Sharpening and Enhancement Algorithm for the Complex Panoramic Image of City Landscape Architecture

Abstract

Abstract When using the current method to sharpen and enhance the edge of panoramic image, it is affected by the noise in panoramic image, resulting in large image standard deviation and mean square error, low signal-to-noise ratio and peak signal-to-noise ratio, high brightness distortion, and visual information distortion. Therefore, an edge sharpening and enhancement algorithm for the complex panoramic image of landscape architecture is proposed. The principal component analysis method is used to denoise the complex panoramic image of landscape architectures. According to the surface points and detail areas of plant landscape, the panoramic image’s super-resolution reconstruction and template matching are carried out, the overall histogram distribution model of panoramic image is reconstructed, and the self-similarity coefficient of edge sharpened surface points of panoramic image is obtained by tone mapping and color feature decomposition, so that the image edge sharpening is completed. Finally, NLEMD algorithm and Retinex algorithm are combined to enhance the complex panoramic image of landscape architecture. Experimental results show that the proposed algorithm has small image standard deviation and mean square error, high signal-to-noise ratio, and peak signal-to-noise ratio, as well as low brightness distortion and visual information distortion.