.. _Images:

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Digital Images
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.. topic:: Reading Assignment

   Please read chapter 2 of [PIVP]_. We will also review some introductory
   material from chapter 12 of [RVC]_.

.. topic:: Video Resources

    * `What is a Digital Image 
      <https://robotacademy.net.au/masterclass/getting-images-into-a-computer/?lesson=626>`_ 
      by Peter Corke.

    * The first several segments of `Dr. Bobick's videos
      <https://www.youtube.com/playlist?list=PLQgNi_PlCHx3tO8XUz8x86r1aMER0bbu3>`_ 
      provide a good introduction.
      
The slides from the authors will serve as our primary notes.

Summary
=========

.. centered:: An image is a 2-D array of pixels (picture elements).
.. centered:: The pixel values are also called intensity.
.. centered:: An image may be also be described as a 2-D function.

.. describe:: Resolution

    The number of rows and columns in a picture. Often noted as columns X
    rows (width X height); but in MATLAB it is rows X columns, which is how
    the size of an array is described.
    
.. describe:: Axis system (u - column number, v - row number)

    **Origin in Center** some algorithms need point (0, 0) in the center of
    the image. Positive u to right and positive v up.

    **Upper Left** unless an algorithm requires the origin in the center, it
    is often in the upper left. In the literature, the origin is usually
    (0, 0), but in MATLAB it is (1, 1). MATLAB array indexes go from 1 to N.

.. describe:: Color or Gray scale

    Gray scale (monochrome) images have a single value for each pixel. Many
    algorithms for feature extraction can only use one value for each pixel.
    In image processing, we often try to get to a gray scale image
    containing only the relevant information needed.

    Color picture contain three gray scale images -- one each for red,
    green, and blue.

    Logical (binary or black-and-white) images are a logical true (1) or
    false (0) for each pixel. Because of the simplicity, they are often
    needed for feature extraction. Algorithms such as segmentation produce
    logical images.

.. describe:: Pixel data

    **uint8** 8-bit unsigned integer. 0 is black, 255 is white.
    Most image files contain uint8 data.

    **unit16** 16-bit unsigned integer -- less common.

    **double** 64-bit double floating point numbers. 0 is black, 1 is white.
    The MATLAB casting function double() can convert unit8 data to double,
    but don't use it because the range will be 0 to 255, which is not
    expected by image processing algorithms. The IPT and MVTB have utilities
    that convert images to double.
    
.. describe:: Neighborhood

    * 4-neighborhood
    * 8-neighborhood