MIL-HDBK-1300A
format for controlled tagged record extensions can appear in any of several locations within a NITF
file.
5.4.3 Encapsulated extensions. These extensions are structurally similar to the registered extensions in that each has a tag. The tag and, in this case, the tag version are registered with the NTB. Each encapsulated extension appears in its own Data Extension Segment (DES), the minimal structure of which is defined by the NITF. The data in an encapsulated extension are anticipated typically to be defined by a specific standard or product specification (which may or may not be under the control of the NTB). Encapsulated extensions provide a way to incorporate arbitrary, but specified, data products in a NITF file.
5.5 Image processing component.
5.5.1 Bandwidth Compression (BWC). Bandwidth compression reduces the amount of data needed to represent image information. Compression algorithms generally may fall into the class of lossless and numerically lossy algorithms. Lossless algorithms preserve the original image data without any numerical losses. Lossy algorithms inherently introduce numerical changes compared to the original. A general tradeoff exists between the compression rate, that is the number of bits-per- pixel (bpp) required to represent the original data, and image quality. Lower compression rates may result in a more visually objectionable reconstructed image; whereas, higher compression rates may result in visually imperceptible losses in the reconstructed image. The NITFS has defined several compression alternatives: no compression, bi-level compression, ARIDPCM gray scale compression, JPEG compression, vector quantization compression, and user defined compression. The bi-level compression losslessly encodes image and overlay information represented by one bpp. ARIDPCM gray scale compression is a lossy scheme that may be used to compress 8- and 11-bit image information. JPEG provides a lossy algorithm for compressing 8- and 12-bit image data and a lossless
algorithm for compressing all image data. Vector quantization provides a lossy compression algorithm for gray scale and color images of any bit depth. Table I provides application guidance for use of bandwidth compression algorithms.
TABLE I. Application guidance for bandwidth compression algorithms.
Compression Algorithm |
Image Type |
Use |
No compression (IC field code NC or NM) |
All |
When numerical loss of data is not tolerable. When image size is small or when transmission bandwidth is large and compression is not needed. |
User Defined (IC field code C0 or M0) |
User determined |
It is the user's responsibility to ensure that the receiving system has access to the same algorithm to decompress the image. The user defined algorithm should perform better than that of the NITFS specified compression algorithm. |
Bi-level (IC field code C1) |
Binary one-bit per pixel images |
Best on data with large areas (run lengths) of uniform color (graphics, maps, overlay). May increase size of bi-level image data. |
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