La traducción de esta página aún no se ha actualizado a la versión más reciente. Haga clic aquí para ver la última versión en inglés.

Entornos y procesamiento por bloques

Defina entornos y bloques para operaciones de filtrado y de entrada/salida

En determinadas operaciones de procesamiento de imágenes, es necesario procesar una imagen por secciones en lugar de hacerlo toda de una vez. En una operación de entorno deslizante, los píxeles de una imagen se procesan uno cada vez mediante la aplicación sucesiva de un algoritmo al entorno de cada píxel. En el procesamiento en bloques discretos, una imagen se divide en bloques de igual tamaño que no se solapan entre ellos, y el algoritmo se aplica a cada bloque de forma independiente. Después, los entornos y bloques se vuelven a ensamblar para formar la imagen de salida.

Funciones

`blockproc`	Distinct block processing for image
`bestblk`	Determine optimal block size for block processing
`nlfilter`	Operaciones de entorno deslizante general
`col2im`	Rearrange matrix columns into blocks
`colfilt`	Column-wise neighborhood operations
`im2col`	Rearrange image blocks into columns

Clases

ImageAdapter Interface for image I/O

Temas

Neighborhood or Block Processing: An Overview
Divide an image into sections, called blocks or neighborhoods, to reduce the memory needed to process the image.
Sliding Neighborhood Operations
A sliding neighborhood operation is performed one pixel at a time using information about the pixel’s neighborhood.
Distinct Block Processing
Distinct block processing divides an image into nonoverlapping rectangular sections that can be processed individually.
Block Size and Performance
Using larger block sizes reduces overall computation time but requires more memory to process each block.
Use Column-wise Processing to Speed Up Sliding Neighborhood or Distinct Block Operations
Reshape sliding neighborhoods and distinct blocks to reduce the execution time of processing an image.
Perform Block Processing on Image Files in Unsupported Formats
To work with image data in file formats not supported by block processing functions, construct a class that manages files based on region.
Parallel Block Processing on Large Image Files
If you have a Parallel Computing Toolbox™ license, you can take advantage of multiple processor cores on your machine to improve the performance of blockproc.

Ejemplos destacados

Block Processing Large Images

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

Abrir script en vivo

Compute Statistics for Large Images

Compute statistics from a large image, and then use that information to more accurately process the image blockwise.

Abrir script en vivo