• Judith Varshini J C
• Piramu M

The new generation of Earth observation sensors with high spatial resolution can provide detailed information for change detection. The widely used methods for high-resolution image change detection rely on textural/structural features. However, these spatial features always produce high-dimensional data space since they are related to a series of parameters, e.g., window sizes and directions. Machine learning methods are also commonly employed, but their performances are subject to the quantity and quality of the training samples, and hence, much effort should be made to collect the high-quality samples. To address these problems, in this work, a novel multi index automatic change detection method is proposed for the high-resolution imagery. First the image is clustered into group of regions by using Fast and Robust Fuzzy C-means Clustering (FRFCM) algorithm. Then the change detection scheme is applied with LANSAT 8 spectral bands. The change detection model is carried out automatically without using training samples since the information indexes can directly indicate the primitive urban classes. The multi-index representation refers to the enhanced vegetation index, the water index, and the recently developed morphological building index. Experiments were conducted on the multi temporal LANSAT 8 images over southern Tamilnadu by the proposed method. Finally the change detection map has been shown to identify the changed regions.

Fast and Robust Fuzzy Clustering Algorithm (FRFCM), textural/structural features

"Remote Sensing Image Classification And Change Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.355-372, March-2019, Available :http://www.jetir.org/papers/JETIR1903E54.pdf

"Remote Sensing Image Classification And Change Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp355-372, March-2019, Available at : http://www.jetir.org/papers/JETIR1903E54.pdf