LERC - Limited Error Raster Compression
What is LERC?
LERC is an open-source image or raster format which supports rapid encoding and decoding for any pixel type (not just RGB or Byte). Users set the maximum compression error per pixel while encoding, so the precision of the original input image is preserved (within user defined error bounds).
The LERC C API
||Computes the buffer size that needs to be allocated so the image can be Lerc compressed into that buffer. The size is accurate to the byte. This function is optional. It is faster than
||Compresses a given image into a pre-allocated buffer. If that buffer is too small, the function fails with the corresponding error code. The function also returns the number of bytes written.|
||Looks into a given Lerc byte blob and returns an array with all the header info. From this, the image to be decoded can be allocated and constructed. This function is optional. You don't need to call it if you already know the image properties such as tile size and data type.|
||Uncompresses a given Lerc byte blob into a pre-allocated image. If the data found in the Lerc byte blob does not fit the specified image properties, the function fails with the corresponding error code.|
||Uncompresses a given Lerc byte blob into a pre-allocated image of type double independent of the compressed data type. This function was added mainly to be called from other languages such as C# and Python.|
To support the case that not all image pixels are valid, a mask image can be passed. It has one byte per pixel, 1 for valid, 0 for invalid.
See the sample program
src/LercTest/main.cpp which demonstrates how the above functions are called and used. Also see the two header files in the
include/ folder and the comments in there.
About multiple bands, or multiple values per pixel. This has changed with Lerc version 2.4. Before, you could either store each band into its own Lerc byte blob which allowed you to access / decode each band individually. Lerc also allowed to stack bands together into one single Lerc byte blob. This could be useful if the bands are always used together anyway. Now, since Lerc version 2.4, you can additionally store multiple values per pixel interleaved, meaning an array of values for pixel 1, next array of values for pixel 2, and so forth. We have added a new parameter "nDim" for this number of values per pixel.
When to use
In image or raster compression, there are two different options:
compress an image as much as possible but so it still looks ok (jpeg and relatives). The max coding error per pixel can be large.
prioritize control over the max coding error per pixel (elevation, scientific data, medical image data, ...).
In the second case, data is often compressed using lossless methods, such as LZW, gzip, and the like. The compression ratios achieved are often low. On top the encoding is often slow and time consuming.
Lerc allows you to set the max coding error per pixel allowed, called
"MaxZError". You can specify any number from
0 (lossless) to a number so large that the decoded image may come out flat.
In a nutshell, if jpeg is good enough for your images, use jpeg. If not, if you would use png instead, or gzip, then you may want to try out Lerc.
How to use
testData/. There is also a precompiled Windows dll and a Linux .so file under
How to use without compiling LERC
Check out the Lerc decoders in
OtherLanguages/. You may need to adjust the paths to input data and the dll or .so file. Other than that they should just work.
How to compile LERC and the C++ test program
build/Windows/MS_VS201X/Lerc.slnwith Microsoft Visual Studio. We have upgraded to VS2017.
- Pick x64 (dflt) or win32.
- Build and run.
build/Linux/CodeBlocks/Lerc/Lerc_so.cbpusing the free Code::Blocks IDE for Linux.
- Build it. Should create
- Build and run.
LERC can also be used as a compression mode for the MRF format via GDAL release 2.1 or newer.
works on any common data type, not just 8 bit: char, byte, short, ushort, int, uint, float, double.
works with any given MaxZError or max coding error per pixel.
can work with a byte mask that specifies which pixels are valid and which ones are not.
is very fast: encoding time is about 20-30 ms per MegaPixel per band, decoding time is about 5 ms per MegaPixel per band.
compression is better than most other compression methods for larger bitdepth data (int types larger than 8 bit, float, double).
for 8 bit data lossless compression, PNG can be better, but is much slower.
in general for lossy compression with MaxZError > 0, the larger the error allowed, the stronger the compression. Compression factors larger than 100x have been reported.
this Lerc package can read all (legacy) versions of Lerc, such as Lerc1, Lerc2 v1, v2, v3, and the current Lerc2 v4. It always writes the latest stable version.
The main principle of Lerc and history can be found in doc/MORE.md
Some benchmarks are in doc/LercBenchmarks_Feb_2016.pdf
The codecs Lerc2 and Lerc1 have been in use for years, bugs in those low level modules are very unlikely. New in Lerc version 2.4 is more rigorous checking against buffer overrun during decoding. If those checks contain a bug then this might trigger the decoder to fail unexpectedly.
Send an email to email@example.com
Copyright 2015-2018 Esri
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