Analysis on Application of Image Processing in Monitoring of Crop Growth

Enhancing agricultural operations through the use of image processing tools has become a potential option. By conducting a thorough analysis of the body of research, developing and implementing image processing algorithms, this study investigates the usefulness of image processing in agriculture. Agricultural fields are the source of spectral and spatial data that are collected by remote sensing technologies as well as by digital cameras. To improve the quality of obtained images, preprocessing procedures such as atmospheric correction, radiometric calibration, and image registration are used. Meanwhile, feature extraction and classification techniques are applied to quantify pertinent crop characteristics and classify land cover classes. The study assesses crop health, phenology, and production using image-derived information, evaluating its accuracy and dependability through field-based validation and comparison analysis.