Image Processing Toolbox

Types of Block Processing Operations

Using these functions, you can perform various block processing operations, including sliding neighborhood operations and distinct block operations.

• In a sliding neighborhood operation, the input image is processed in a pixelwise fashion. That is, for each pixel in the input image, some operation is performed to determine the value of the corresponding pixel in the output image. The operation is based on the values of a block of neighboring pixels.
• In a distinct block operation, the input image is processed a block at a time. That is, the image is divided into rectangular blocks, and some operation is performed on each block individually to determine the values of the pixels in the corresponding block of the output image.

In addition, the toolbox provides functions for column processing operations. These operations are not actually distinct from block operations; instead, they are a way of speeding up block operations by rearranging blocks into matrix columns.

Note that even if you do not use the block processing functions described in this chapter, the information here may be useful to you, as it includes concepts fundamental to many areas of image processing. In particular, the discussion of sliding neighborhood operations is applicable to linear filtering and binary morphological operations. See Chapter 6, Linear Filtering and Filter Design and Chapter 9, Binary Image Operations for information about these applications.

Neighborhood and Block Operations

Sliding Neighborhood Operations