Significance of building an image pyramid

Image pyramid structure: it refers to the storage and display of different resolutions based on users' needs under the same spatial reference, forming a pyramid structure with a coarse to fine resolution and a small to large data volume. The image pyramid structure is used for image encoding and progressive image transmission. It is a typical hierarchical data structure and is suitable for the Multi-Resolution Organization of raster data and affected data, it is also a Lossy Compression Method for raster data or image data.

"Layered" refers to the index of the image pyramid (pyramid. The basic idea is to generate a pyramid from the bottom of the sample, and take a certain level of the pyramid as the operation object as needed to improve the overall efficiency. Of course, like other things in this world, efficiency improvement comes at a cost. This is the extra space overhead brought about by tower construction. The more levels it creates, the more convenient it is to query, of course, the larger the data redundancy is.

If a pyramid is created for a large Raster image, these images can be quickly displayed. In addition to display on the screen, the pyramid also contains a lot of other information. If there is no pyramid, you need to access the raster dataset during display, and then perform a lot of calculations to select which raster pixels are displayed. Pyramid is a method for storing raster images in a copy mode that reduces resolution step by step. By selecting a resolution similar to the display area, you only need to perform a small amount of queries and calculations to reduce the display time.

Every time you use ArcGIS to open an image, you will see creating pyramids in the status bar. At this moment, you are building an image's gold tower. Currently, portal applications such as Google Map, visual earth, And mapbar use to pre-process the map into an image pyramid, and split the chunk into four-tree codes. The maptile is dynamically called during the zoom and Pan operations. This architecture omits out the components that consume a lot of server performance.

Each layer of the image pyramid has its resolution, so according to your current operation, such as amplification (whether it is a pull box or a fixed proportion), zoom out, roaming (this operation does not involve changes to the image resolution) to calculate the image resolution required for this operation and the geographic coordinate range that will be displayed within the current view range, then, the resolution is matched with the resolution of the created image pyramid. The resolution of the layer of the image pyramid is the closest to that of the image pyramid, in addition, based on the range that the current view should display after the operation, you can find the number of corresponding images on the layer pyramid, and then read the values of the corresponding pixels.