An Novel Grayscale Image Segmentation Method based on 2D Entropy and Particle Swarm Optimization
WEI Yanjun ZHAO Xin - · International Journal of Digital Content Technology and its Applications · 2012
The one-dimension entropy method only considers gray information. Spatial information of pixels is ignored. Therefore the spatial conjoint pixels can’t take into account in image. Otherwise, it has poor anti-noise capability. Two-dimension entropy method considers the spatial information and gray information, but the computing quantity is large. Improved 2D maximum entropy threshold segmentation method based on PSO is called PSO-SDAIVE algorithm. This algorithm not only considers the spatial information, but also considers the gray information and decreases the computing quantity. Otherwise, the neighboring pixel control parameter is set. The overly-smoothness of images can be avoided.