This learning path will introduce you to the visualization and radiometric operations domain of the Earth Observation which basically deals with the different perceptions regarding colours. Thus it will explain to you how we individually perceive colour, to help us understand how to produce optimal images from multispectral data perspectives for their proper interpretation.
The first concept for our consumption in this learning path is EM radiation which looks at the energy flux in space.
Tri-stimuli theory which states that there are three (3) degrees of freedoms in the description of a colour is the next concept you will introduced in this learning path.
It is equally important for us to look at colour systems and in this learning path we will pay attention at Subtractive colour system, which is based on three(3) printing colours such as Yellow, Magenta and Cyan (YMC). Subtractive colour system is also used for colour photography.
Mostly digital images are displayed using Grey Scale and this takes us to "Image Display" as a key concept for our consideration in this path. Digital images can be raw data such as that obtained with a panchromatic camera or data obtained by scanning a B&W photograph or a single band of a multi-band image.
For displaying data which have not reflection measurements, for example thermal infrared data, Pseudo Colour is required-- hence our consideration of that here.
One concept worth for our consideration in this learning path is Colour Composite.
True colour in other parlance known as Natural colour is the next item for discussion in this learning path. True colour is made, where the RGB channels relate to the red, green and blue of wavelength band of a camera or multispectral camera.
Basically for the proper displaying of and enhancing to images, approaches to elementary image processing need to be considered-- *Histogram operations; * Filtering
Our next item for discussion is "Histograms" which reveal the radiometric properties of digital images to describe the distribution of the pixel values of the images.
One element in image processing worth considering in this learning path is the term Histogram operations, which aims at enhancing global contrast and suppressing unwanted image details.
Another element in image processing is the term Filtering, which aims at enhancing local contrast (edge enhancement) and suppressing unwanted image details.
Noise reduction is an important element in image processing worth of consideration in this learning path because it helps to reduce the effect of speckle by the application of a filter.
This takes us to image processing techniques. First f all, one of such techniques worth considering in this learning path is Edge Detection as a technique in finding the boundaries of objects within images. Filter kernels for edge detection include: * x-gradient filter; * y-gradient filter; and all-directional filter.
Apart from Edge Detection, another image processing technique worth our consideration in this learning path is Edge Enhancement where filtering is done to emphasize local differences in DN values by increasing contrast, example for linear features such as roads, canals and geological faults. It is done using edge enhancing filter which calculates the differences between the central pixel and its neighbours.
In this learning path, we now zoom into radiometric operations to look at operations on image data which uses and/ or changes the value of the pixels, assuming their location is correct.
Raw data collected with a sensor may be inherent with errors and noise which need to be corrected and this takes us to correction of imperfections of a sensor. Typically problems requiring "cosmetics" corrections include: periodic line dropouts; line striping; random noise or spike.
For removal of of sky radiance effects from raw data which may be beneficial to many applications of space-borne RS, Haze corrections is required, hence that becomes our next step subject of discussion.
In this learning path, we will also explain the term "Sun Elevation Correction"which is used to normalize images a if they were taken with the sun at its zenith.
Finally, we will look at the relevance of atmospheric correction.