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Image Processing Remote Sensing Signal

by Aakash Singha

Image Processing Remote Sensing Signal , is an art of extracting information from an object obtained with the help of remote sensing signal through image processing. Remote sensing signal s are acquired or…


Image Processing Remote Sensing Signal , is an art of extracting information from an object obtained with the help of remote sensing signal through image processing. Remote sensing signal s are acquired or captured through a system which is board on the platform. The collected signals are then converted into a digital format which is known as image. Images are always come to us in digital form. These images are then taken for further image processing .

 

Image Processing Remote Sensing Signal image processing includes the study of remotely sensed data through the process of detecting, identifying, classifying, measuring and evaluating the significance of physical and cultural objects and their spatial relationship. Image processing is required to do for image interpretation.

 

Image processing is any form of information processing for which the input is an image such as photographs or frames of video. In the image processing techniques images are treated as a two dimensional signal. Images are mainly available in two format-

  • Vector form- In vector format images are mainly represented as line, point, and polygon. All type of image processing techniques are done on the digital form.
  • Raster form- In raster form images are represented as a array of grid. Each pixel in the grid is represented DN value. It is necessary to convert raster format for image processing .Image processing techniques are mainly two type- 
  • Visual image processing – The processing include visually process the image or visually analysis the image. Visual image processing techniques include identify the feature in the image with the help of texture, shape, identify the object with the help of shadow, color, tone, structure, size and weathering phenomenon. Visual image processing techniques is appropriate for the basic image interpretation.
  • Digital image processing – Digital images are represented as an array of grid. The grid represent some spatial distribution of a certain field parameters such as electromagnetic radiation, temperature, or some geophysical or topographical elevation. Each DN value represent the average radiance or brightness value of the features in a relatively small area within a scene. DN values or brightness values are normally represented 0 to 255. According to pixel size the amount of information is increase or decrease.

Digital image data is required to convert for interpretation purposes. The characteristics of the image is depending upon the variations in brightness on photographic films. The features which are reflecting more energy will appear bright in the image and less energy will appear black in the image. Digital remote data are often organized using one of the three common formats used to organize image data. A image consisting of four spectral channels is often visualized as four superimposed images with corresponding pixels in one band registering exactly to those in the other band. The three common formats are:

  • Band Interleaved by Pixel (BIP)
  • Band Interleaved by Line (BIL)
  • Band Sequential (BQ)

Image Processing Remote Sensing Signal , all image processing techniques are based on image which are represented in digital format. Remote sensing techniques are involved in capturing signals which are reflected by the spatial objects or features. Each spatial object or feature in the earth has individual electromagnetic spectrum because each feature differs in mineral composition. The electromagnetic spectrum is often known as Remote sensing signals . With out any direct contact the satellites remotely capture signals so it is known as Remote sensing.

 

Image processing remote sensing signal s are used in the fields like engineering, scientist and researches. It is also useful in the disciplines like aerospace, defense, remote sensing, biotechnology, medical imaging, scientific imaging and material science.

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