Steps in Digital Image Processing: Pre-Processing, Display and Enhancement, and Information Extraction (Especially for GATE-Geospatial 2022)

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Digital image process is a collection of techniques for the manipulation of digital images by computers. The raw data received from the imaging sensors on the satellite platforms contains flaws and deficiencies. To overcome these flaws and deficiencies in order to get the originality of the data, it needs to undergo several steps of processing. This will vary from image to image depending on the type of image format, the initial condition of the image and the information of interest and the composition of the image scene Digital Image Processing undergoes three general steps:

  • Pre-processing
  • Display and enhancement
  • Information extraction

1. Pre-Processing

Pre-processing consists of those operations that prepare data for subsequent analysis that attempts to correct or compensate for systematic errors. The digital imageries are subject 3d to several corrections such as geometric, radiometric and atmospheric, though all these corrections might not be necessarily be applied in all cases. These errors are systematic and can be removed before they reach the user. The investigator should decide which pre-processing techniques are relevant on the basis of the nature of the information to be extracted from remotely sensed data. After pre-processing is complete, the analyst may use feature extraction to reduce the dimensionality of the data. Thus, feature extraction is the process of isolating the most useful components of the data for further study while discarding the less useful aspects (errors, noise etc) . Feature extraction reduces the number of variables that must be examined, thereby saving time and resources.

2. Image Enhancement

This operation is carried out to improve the interpretability of the image by increasing apparent contrast among various features in the scene. The enhancement techniques depend upon two factors mainly

  • The digital data (i.e.. with spectral bands and resolution)
  • The objectives of interpretation

As an image enhancement technique often drastically alters the original numeric data, it is normally used only for visual (manual) interpretation and not for further numeric analysis. Common enhancements include image reduction, image rectification, image magnification, transect extraction, contrast adjustments, band rationing, spatial filtering, Fourier transformations, principal component analysis, and texture transformation.

3. Information Extraction

Information Extraction is the last step toward the final output of the image analysis, after pre-processing and image enhancement the remotely sensed data is subjected to quantitative analysis to assign individual pixels to specific classes. Classification of the image is based on the known and unknown identity to classify the remainder of the image consisting of those pixels of unknown identity. After classification is complete, it is necessary to evaluate its accuracy by comparing the categories on the classified images with the areas of known identity on the ground. The result of the analysis consists of maps (or images) , data and a report. These three components if the result provides the user with full information concerning the source data, the method of analysis and the outcome and its reliability.

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