unsupervised non-parametric multi-component image segmentation method

摘要

A programmed and developed a GUI for an approach which consists of multiple improved techniques or algorithms for an unsupervised and efficient segmentation of multi-component images (multiple spatial and spectral resolutions). Objects existing in the images are detected and separated efficiently which makes the process of object separation easier and more accurate. The process is an unsupervised which requires no intervention from the user and no major parameters are required. The choice of these parameters is affected by the quality of the image which in turn affects the result of segmentation. The new method uses an objective function to maximize heterogeneity (maximize homogeneity inside each object or cluster) between the segmented objects and to reduce the over-segmentation. The new method can provide high speed and acceptable accuracy or normal to slow speed with high accuracy depending on the criticality of the application and the objective of using the final results.

主权项

1. A method for multi-component image segmentation comprising:
a. multi-spectral, multi-spatial, multi-temporal image data; b. Enhancement of the image by filtering noise c. Enhancement the contrast of the image d. Edge enhancement in the image; e. a method to segment the image using Genetic algorithm (GA) only f. a method to segment the image using Self-Organizing Maps (SOMs) only g. an approach that combine the previous two methods