Object-based classification vs. Pixel-based classification.
Object-based classification: Classification is done on a localized group of pixels, taking into account the spatial properties of each pixel as they relate to each other.
This study made a comparison of an object-based classification with supervised and unsupervised pixel-based classification. Two multi-temporal (leaf-on and leaf-off), medium-spatial resolution SPOT-5 satellite images and a high-spatial resolution color infrared digital orthophoto were used in the analysis.
The object-based classification (90.4%) outperformed the pixel-based classification (67.6%) in overall accuracy for their original image; however, in their test image, the differences between the object-based and pixel-based approaches was reduced to less than 10% (95.2 and 87.8%, respectively).
The same principle holds true for classifying pixels as it does image objects or segments; the specific algorithm determines how the pixels are grouped together based on a given set of statistical rules.
Per-pixel classification using backpropagation neural network classifier The image was classified into 9 prominent classes covering a majority of the land cover features, as shown in the legend of figure 2. Both Object based and Pixel based (using spectral features for classification) approaches were used to classify the image.
What is the difference between object detection and object classification? Ask Question Asked 4 years, 8 months ago.. it relates to the object classification task. If you have to define coordinates of an object on the image, then it is the object detection task.. Making statements based on opinion; back them up with references or personal.
Comparison of pixel-based and object-oriented classification approaches using Landsat-8 OLI and TIRS spectral bands.
Generally, the results show that LiDAR intensity data can be used for land cover classification. An overall accuracy of 63.5% can be achieved using the pixel-based classification technique. The overall accuracy of the results is improved to 68% using the object- based classification technique.
Pixel based object recognition, like the name says, works by analyzing the individual pixels of an image.For example: You analyze an image with a lot of different shades of blue and some grey pixels - you might assume that this is the picture of a plane in the sky or a ship in the water.
Image analysis by Object-Based Classification (OBC): Object based classification is different from the pixel based classification approach as it works on the group of pixels instead of direct pixels. OBC has two steps: (i) Image Segmentation to generate segmented image and (ii) classification of segmented image.
While pixel-based image analysis is based on the information in each pixel, object-based image analysis is based on information from a set of similar pixels called objects or image objects.
Some consider that the object-based classification is superior to the pixel- based even without using high-resolution images (Blaschke and Strobl, 2015), while other results show that the pixel.
Comparison of pixel based and object based classification over images with various spatial resolutions Yan Gao UNAM, Mexico October, 2008 GEOBIA2008 Objective By comparing the object based classification results with those produced by the pixel-based method over images with various spatial resolutions, this work intends to find out how spatial.
