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邻域和数据块处理

R2026a

定义用于滤波和 I/O 运算的邻域和数据块

某些图像处理运算需要分段处理图像，而不是一次处理整个图像。滑动邻域运算通过对每个像素邻域应用算法，以一次一个像素的方式处理图像。在另一种数据块处理中，图像被分成大小相等且不重叠的数据块，并对每个不同数据块应用算法。然后，对邻域和数据块进行重组以形成输出图像。

函数

`blockproc`	图像的非重复块处理
`bestblk`	Determine optimal block size for block processing
`nlfilter`	General sliding-neighborhood operations
`col2im`	Rearrange matrix columns into blocks
`colfilt`	Column-wise neighborhood operations
`im2col`	将图像块重新排列为列
`blockedImage`	Big or multiresolution image made from discrete blocks
`apply`	Process blocks of blocked image

Block Processing: An Overview
Divide an image into sections, called blocks, to reduce the memory needed to process the image.
Block Size and Performance
Using larger block sizes reduces overall computation time but requires more memory to process each block.
Create Adapter to Read Unsupported Image Formats for Blocked Processing
To work with image data in file formats that are not natively supported by the blockedImage object, create a custom adapter that reads blocks of data.

Perform edge detection on a large image by reading, processing, and writing the results back to disk, one block at a time.

Calculate global statistics from a blocked image by aggregating the statistics of individual blocks.