Remote Sensing - a tool for environmental observation

The advantage of this method is that it is the

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The advantage of this method is that it is the easiest and fastest method and that the original data values are preserved. 2. Bilinear interpolation: the new pixel value is based upon the distances between the new pixel location and the four closest pixel values in the old grid (inverse distance interpolation). A disadvantage of this method is that the new DN-values are smoothed. 3. Cubic convolution: the new pixel value is computed from the 16 (or even 25) pixel values in the old grid closest to the new location. Lillesand and Kiefer (2000) show the effect of the different resampling methods on a MSS image on page 476. Note the ‘stair stepped’ effect in the nearest neighbour resampling and the smoothing effect in the two other methods.
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70 A. B. C. D. Figure 5.9 Resampling techniques: A) Open circles indicate reference grid from input image (and location determined from topographical map or GPS). B) Nearest Neighbourhood resampling: each estimated (new) value receives the value of the nearest point on the reference grid. C) Bilinear interpolation: each estimated value in the output image is formed by calculating the weighted average (inverse distance) of the four neighbours in the input image. D) Cubic convolution: each estimated value in the output matrix is found by computing values within a neighbourhood of 16 pixels in the input image.
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71 5.5 Image Enhancement Image enhancement is the modification of a digital image to alter its impact on the viewer. Generally enhancement is carried out after image restoration. Image enhancement may comprise contrast improvement (by stretching), edge enhancement by digital filtering and information extraction techniques such as ratioing or principal component transformation. Contrast Enhancement Techniques for improving image contrast are the most widely used in image processing. The sensitivity range of the Landsat sensors was designed to record a wide range of terrains from water bodies to bright ice fields. As a result few scenes have a brightness covering the full sensitivity range of the sensor. To produce an image with optimum contrast, it is important to use the entire brightness (and colour) range of the monitor. The histogram of the image provides information on the used brightness range. A histogram of a digital image is a x-y diagram showing the frequency of occurrence (number of pixels) of individual values (digital numbers). The histogram information provides useful information to stretch optimally the grey- tones or colours over the digital values (figure 5.10). Linear contrast stretch is the simplest contrast enhancement method. Extreme black and extreme white are assigned to the smallest, respectively the largest DN value in the histogram. To fasten the process a lookup table or LUT is often used. Non-linear stretch or special stretch, this type of stretch uses a e.g. user-defined part of the histogram or a non-linear e.g. gaussian curve to perform a stretch on the image (figure 5.10). Histogram stretch: image values are
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