Pre-processing of drought/water stress detection chlorophyll fluorescence wheat images for efficient segmentation

The data consist of a file system-based data of Raj 3765 variety of wheat. There are twenty-four chlorophyll fluorescence images (Control and Drought) that have been captured for a period of sixty days. A total of (1440 x 2) images are used for this research work. The generated chlorophyll fluorescence set is subjected to various pre-processing operations including noise removal, and contrast enhancement. Pre-processed images are subjected to segmentation to increase water stress detection accuracy for automation in machine learning algorithms