Errors involved in digital image capturing and processing can either be systematic or random. Systematic errors are classified into geometric distortions, spectral errors and distortions. Geometric distortions are caused by sensor-Earth geometric variations which affects the position of a pixel relative to other pixels,. In digital images, the pixel position is compared to the other pixels in the scene and the absolute position of the pixel relative to real coordinates in latitudes and longitudes. Geometric distortions can render the image and the information expected to be derived from the image as useless,. This is because the image is sometimes compared to other data set to produce meaningful information.
Geometric distortions occur due to several reasons including altitude and platform attitude changes, rotation of the Earth, detector delay, and panoramic distortion among others,. If left unresolved, the distortions can render the image useless. Spectral errors and distortion are caused by the sensors, topography, the atmosphere, and the angle of the sun,. System errors can often lead to changes in the image such as causing defective data along the image scan line,. When the sensitivity of the image acquisition depends on the position in the image in some cases, changes in position and other geometric distortions may affect the image brightness. Systematic degradation in this case may occur as a result of uneven sensitivity of light sensors and object illumination.
Systematic errors in digital images can be corrected using pre-processing techniques. Unsystematic errors can also be corrected and minimized, making the use of digital images efficient and effective. Pre-processing refers to the functions that are processed prior to the actual analysis of the data,. These methods include radiometric corrections and geometric corrections. Radiometric corrections correct the spectral errors that may be caused by uneven sensors and the angle of the sun among other causes. This involves the reconstruction of the calibrated values and can be done in the ground stations. For example, a systems error that leads to defective data along a scan line can be corrected through radiometric correction by replacing the line with pixel values of the neighboring line either from above or below,.
Geometric corrections are used to correct geometric distortions such as those caused by sensor-Earth geometry variations. It is possible to correct the predictable distortions by accurate modeling of the sensor and platform motions,. It is also important to model the platform’s geometric relationship with the Earth correctly in order to avoid geometric distortions. However, some causes of errors may turn out to be difficult to predict and prevent or correct. For example, it is difficult to account for changes in the attitude mathematically. In order to deal with such error, image rectification is necessary. This involves correcting an image in order to make it conform to the map and other images and be represented on a planar surface,. Rectification is important when there is a need to estimate accurate measurements from the image. Image rectification can be achieved through geometric transformation. Geometric registration can also be used to correct random errors on digital images. It can be done through the identification of image coordinates and resampling. Identification of image coordinates involves the matching of distorted images to their correct positions on the map.
Work Cited
Malgorzata, Verőné Wojtaszek. "Data acquisition and integration 6., 6 Remote Sensing." Tankonyvtar.hu (2010). <http://www.tankonyvtar.hu/en/tartalom/tamop425/0027_DAI6/ch01s04.html>.
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