What is object based image segmentation?
Object-Based Image Analysis (OBIA) segmentation is a process that groups similar pixels into objects. What segmentation does is replicate what your eyes are doing. But with these segmented objects, you use their spectral, geometrical, and spatial properties to classify them into land cover.
What is object based approach?
In the object-oriented approach, the focus is on capturing the structure and behavior of information systems into small modules that combines both data and process. The main aim of Object Oriented Design (OOD) is to improve the quality and productivity of system analysis and design by making it more usable.
How to use Google Earth for image classification?
In this post we’ll perform a classification of high resolution satellite images using GEOBIA (Geographic Object Based Image Analysis) on Google Earth Engine. The satellite image to be classified is an image from the National Agriculture Imagery Program (NAIP), which contains the bands B (Blue), G (Green), R (Red) and N (Near Infrared).
Which is an object in Google Earth Engine?
Image objects are sets of connected pixels having the same integer value. Categorical, binned, and boolean image data are suitable for object analysis. Earth Engine offers methods for labeling each object with a unique ID, counting the number of pixels composing objects, and computing statistics for values of pixels that intersect objects.
How to perform object based image classification in Google?
How do I convert the ‘edges’ image to a 1-band raster with N objects, with the individual objects being grouped by similar spectral values? Here is an EE OBIA example based on Noel Gorelick’s recent image segmentation presentation and example code ( available here ).
How to perform image segmentation in Google Earth?
I am trying to perform an image segmentation using Google Earth Engine. I have performed OBIA in the past using python and scikit-image (skimage.segmentation.felzenszwalb) , but not sure how to do this using GEE.