(A) images and image engineering

Image: The various observing systems in different forms and means of observation of the objective world obtained, directly or indirectly to the human eye and thus produce visual perception of the entity. Human information obtained from outside (the objective world) about 75%.

The image represents: 2-D array \ (F (X, Y) \) , where \ (x, y \) is the position of the 2-D space coordinate points, \ (F \) representative image in \ ((x, Y) \) properties at \ (F. \) values, e.g., in the gray scale image is represented by gray.

The image is an aggregate of many image elements:

  • 2-D images: pixels (Pixel Element), i.e. pixel
  • 3-D images: voxel (Volume Element), i.e., voxel

\ [F (x, y) \ rightarrow f (x, y, z), f (x, y, t) \\ Note: f (x, y, z) represents a perspective view, f (x, y, t) indicates that the video \]

Image Engineering can be divided into three levels:

  • Image processing (Image -> Image)
  • Image analysis (Image -> data)
  • Image understanding (Image -> interpretation)

Image engineering and related disciplines in the field of contact and differences:

  • Graphics: the former refers to the scientific data with graphics, charts, graphics and other forms of expression graphics computer imaging studies is how to use computer technology to produce these forms
  • Pattern Recognition: An attempt to abstract image into categories described in the available symbol
  • Computer Vision: The main emphasis on the use of computers to achieve human visual function, the current research mainly in combination with image understanding

Central problem is to simplify the image analysis of several megabytes grayscale image or a color image into a number of interesting and useful only numbers, from the image, wherein the target of interest is detected, extraction, expression, and measurement is described, so as to obtain objective information, the results of the process output data and technology.

Image Process Application Example:

  • Image Acquisition: from the scene to the image
  • Pretreatment: distortion correction data generated by image processing (reversible)
  • Recovery: filters the data to reduce the effects of noise and distortion (non-inverted)
  • Segmentation: The image is decomposed into a target to be analyzed and other background
  • Measurement: measured data from the digitized "analog" in nature
  • Visualization: comparing the measured results to the user in a useful and readily understood manner represented

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Origin www.cnblogs.com/xxxxxxxxx/p/11494149.html