Abstract: 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.