• Aparna Joshi
• Asst. Prof. Lalita Randive

This paper presents Image matching and registration method that is invariant to scale, rotation, translation and illumination changes. The method is named as Scale Invariant Feature Transform (SIFT). This algorithm will detect and describe image features such as contours, points, corners etc. SIFT descriptors are the characteristic signature of the feature. The features calculated from the image to be registered should be distinctive and then it can be matched. It can be useful in object recognition, image mosaicing, 3 D reconstruction and video tracking. The simulation results shows that this algorithm works well in all types of cases having scale and rotation difference, it also register the object having occlusion and clutter background. Due to good invariance of scale, rotation, illumination, SIFT (Scale Invariant Feature Transform) descriptor is commonly used in image matching. The steps of extracting SIFT feature are analyzed in detail, and SIFT Key-point location is optimized.

SIFT, Key Descriptors, Image Processing

"Implementing SIFT for Remote Sensing Image Registrations ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 12, page no.a737-a747, December-2021, Available :http://www.jetir.org/papers/JETIR2112089.pdf

"Implementing SIFT for Remote Sensing Image Registrations ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 12, page no. ppa737-a747, December-2021, Available at : http://www.jetir.org/papers/JETIR2112089.pdf