Some compression formats, such as JPEG 2000, are CPU-intensive to decompress. Amount of processing power required to decompress the imageĬompression requires that the system decompress the imagery before any processing can be applied.Compressing imagery also increases the CPU load for reading the imagery, and some algorithms are much more CPU efficient than others, so some compression formats are better than others. Lossy compression algorithms can substantially reduce data volumes but add unacceptable artifacts to imagery, especially if it is to be used for analysis. Lossless compression algorithms, such as LZW, can be effectively used to compress imagery that contains a large number of NoData values, but generally provide minimal compression of optical imagery. Such compression substantially reduces the volume of data read from disk and can have a positive influence on performance, especially on systems with slower drive systems. Typically, a natural color image can be compressed 5–10 times with negligible difference in image quality. Imagery compression can substantially reduce the size of the data read. If the data volume to be read is reduced, this can improve performance. By default, ArcGIS writes a tiled TIFF.įor any group of pixels to be processed, those pixels must be read from storage. The TIFF format can be tiled or non-tiled. Most modern file formats are either tiled or include options for tiling. On larger files (more than 3,000 columns), you can use a tiled image format that breaks the image internally into smaller tiles (typically 256x256 pixels), making it faster to access a group of pixels representing a rectangular extent. When the rasters are large and only a small extent of an image needs to be read, the system can skip quickly to the appropriate row in the file, but it will still need to read the complete row due to the way files are broken and read as blocks on disk. In many cases, rasters are stored as an array of pixels on disk. The following five factors have the greatest influence on Performance of the storage system as well as the format of the imageryĬan have a significant effect on the performance of the imaging Scalability for large numbers of large images, ArcGIS reads onĭemand only the appropriate imagery from storage. Many traditional workstation imagery applicationsįirst read the complete image into memoryĪnd then allow a user to make changes to the imageīefore saving it. Lossy or lossless compression in the format conversion is optional. The original data is often then archived. Thisĭoes not involve sampling the imagery or changing the structure, but it does result in dataĭuplication. Interpretation, it is preferable (and sometimes necessary) toĮnsure that the pixel values do not change.Ĭases, it is advisable to change the format of the imagery to make it faster to access. With imagery used for analysis or high-quality Possible artifacts, creation of NoData areas, and issues Projection), this leads to degradation in quality, When imagery is processed so that the pixels are sampled (for example, to change the Generally, it is best to leave imagery in its original form. Information about relevant types of data and how the imagery can be obtained,Īs well as recommendations concerning the format and suitable High-resolution satellite imagery, imagery from frame cameras, or Check out the rest of the image management workflows to find more information about managing a specific type of imagery, such as
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