anchor.diff:  By default MATLAB image matrices convert to `byte[height][width][channels]` Java arrays. However, when converting back to MATLAB there are some additional problems:
   
   * `byte` gets converted to `int8` instead of `uint8`, resulting in an invalid image matrix
  -* changing the type back to `uint8` gets somewhat messy because the `uint8(matrix)` cast would set all negative values to zero, and the alternative `typecast(matrix, 'uint8')` only works on vectors
  -
  -Thus, converting the data to a valid image matrix still required several operations.
  +* changing the type back to `uint8` is somewhat messy because the `uint8(matrix)` cast sets all negative values to zero, and the alternative `typecast(matrix, 'uint8')` only works on vectors
  +
  +Thus, converting the data to a valid image matrix still requires several operations.
   
   [source,matlab]
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positive.code: 
  *5. MATLAB Layout as Shared Memory*
  
  This approach is the same as (4) with the difference that the Java translation layer is bypassed entirely by using shared memory via link:https://mathworks.com/help/matlab/ref/memmapfile.html[memmapfile]. Shared memory is typically used for inter-process communication, but it can also be used within a single process. Running within the same process also simplifies synchronization since MATLAB can access Java locks.
  
  [source,matlab]
  ----
  
negative.code: 
  *4. MATLAB Layout as 1D Pixel Array*
  
  The fourth approach also copies a pixel array, but this time the pixels are already stored as in the MATLAB convention.
  
  [source,matlab]
  ----
  