A remotely sensed image is made up of a rectangular matrix of individual pixels, where each pixel represents a specific ground area. The value of each pixel represents the magnitude of upwelling electromagnetic energy from that given ground area (Mather, 1999). Energy occurs in different wavelengths, and by measuring the energy in different bands or spectra of wavelengths, coming from the same ground area, ground features can be distinguished from each other, as they show typical characteristics in the different bands recorded, e.g. water is different form soil or vegetation.
To distinguish different features in a TM image, the figure below left is of help, as it shows how different features generally display their reflectance values in the different bands of the TM sensor.
Grey scale enhancement
One of the most basic enhancement techniques is the contrast stretch. If the screen is set to display 256 grey scale colours, band3 in leic-tm92 will appear dark, as most values are clustered around the mean value of 29, with the overall values ranging from approximately 21 to 55, taking up only 34 different values or 14% of the full value range (0-255) that can be utilised.
Band rationing means dividing the pixels in one band by the corresponding pixels in a second band. The reason for this is twofold: One is that differences between the spectral reflectance curves of surface types can be brought out. The second is that illumination, and consequently radiance, may vary, the ratio between an illuminated and a not illuminated area of the same surface type will be the same. Thus, this will aid image interpretation, particularly the near-infrared/ red (NIR/R) band ratio.
Bad line replacement
Part of image with missing scan line
Regarding the position of the missing scan line, to find the correct row number, it must considered that the image peak-tm84 has 512 rows and 512 columns according to it’s image info, with coordinates upper left 1/1(y/x) and lower right 512/-510 (y/x).
Since the missing scan line is at x = –200, this is row number 201.
Original image (top), Principal Component Analysis (middle) and Tasselled Cap Transform (bottom)
In the true colour image, with bands 1, 2 and 3, there seem to be little difference between principal component analysis (PCA) and tasselled cap transform (TCT). Even though the colour differs, the same pattern can be discerned.
When performing an unsupervised classification it is necessary to find the right number of classes that are to be found. Too many, and the image will not differ noticeable from the original, too few and the selection will be too coarse.