Lamyaa Taha

The applications of automatic image interpretation Lamyaa Taha

The present study attempts to review the state of art for applications automatic image interpretation in surveying and photogrammetry. The increased information and experience in automatic image interpretation and new technology developed over time increased the number of applications of automatic image interpretation in surveying and photogrammetry. This work reviewed major land cover classification techniques, including pixel based classification techniques, subpixel based classification techniques, and object-based classification methods. The main focus is certainly on the summarization of modern classification methods and the approaches used for improving classification performance. In this article, the emphasis is placed on the current applications of automatic image interpretation in surveying and photogrammetry. It was reported that correct choice of derived features from remotely sensed data (multicues) and the use of appropriate classification technique are needed for classification accuracy improvement. Also edge detection and texture analysis will be explored.