Abstract: The present disclosure relates to the field of image processing and discloses an agricultural advisory system (100) comprising a user device (102) and a cloud server (104). The user device (102) captures a digital image of a scene, receives a sensed data corresponding to scene-related and environmental parameters, and transmits the image and the sensed data to the cloud server. The server (104) stores one or more pre-trained prediction models and a three-dimensional HyperIntelliStack which maps red green blue (RGB) pixel values with hyperspectral reflectance values. The server (104) receives the digital images and the sensed data, transforms the received image made of RGB pixel values into a hyperspectral image using the HyperIntelliStack data structure, computes vegetation indices for each pixel of the hyperspectral image to generate a segmented image, and generates at least one advisory for agriculture and allied areas using the segmented image and one or more prediction models.

Abstract: The present disclosure relates to the field of image processing and discloses an agricultural advisory system (100) comprising a user device (102) and a cloud server (104). The user device (102) captures a digital image of a scene, receives a sensed data corresponding to scene-related and environmental parameters, and transmits the image and the sensed data to the cloud server. The server (104) stores one or more pre-trained prediction models and a three-dimensional HyperIntelliStack which maps red green blue (RGB) pixel values with hyperspectral reflectance values. The server (104) receives the digital images and the sensed data, transforms the received image made of RGB pixel values into a hyperspectral image using the HyperIntelliStack data structure, computes vegetation indices for each pixel of the hyperspectral image to generate a segmented image, and generates at least one advisory for agriculture and allied areas using the segmented image and one or more prediction models.