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).
This repository contains both a C++ library for encoding/decoding images and JavaScript and Python codecs for decoding LERC files.
| Function | Description |
|---|---|
bool ComputeBufferSize(...) |
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 Encode(...). It can also be called to decide whether an image or image tile should be encoded by Lerc or another method. |
bool Encode(...) |
Compresses a given image into a pre-allocated buffer. If that buffer is too small, the function fails and returns false. The function returns the number of bytes written. |
bool GetLercInfo(...) |
Looks into a given Lerc byte blob and returns a struct 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. |
bool Decode(...) |
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 and returns false. |
To better support the case that not all image pixels are valid, the BitMask class is provided. It permits easy and efficient checking and setting pixels to valid / invalid.
See the sample program src/LercTest/main.cpp which demonstrates how the above functions and classes are called and used. Also see the two header files in the include/ folder and the comments in there.
One more comment about multiple bands. You can either store each band into its own Lerc byte blob which allows you to access / decode each band individually. Lerc also allows to stack bands together into one single Lerc byte blob. This can be useful if the bands are always used together anyway.
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.
Lerc can be run anywhere without external dependencies. This project includes a test sample of how to use LERC directly. LERC can also be used as a compression for the MRF format via GDAL release 2.1 or newer.
- Open
src/Lerc/Lerc.slnwith Microsoft Visual Studio. We have used MSVS 2013. - Build the
Lerc.dll. Pick x64 or Win32 according to your system. Copy the resultingLerc.libinto thelib/folder. - Open
src/LercTest/LercTest.sln. - Build the test application
LercTest.exe. Again, pick x64 or Win32. - Copy the
Lerc.dllfrom above next toLercTest.exe. - Run it.
- Go to
src/Lerc - Call
make. This should createlibLerc.so. - Go to
src/LercTest. In the makefile, adjust the paths at the top as needed. Call make. This should createmain.out.- Run it.
-
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 bit 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, and the current Lerc2 v3. 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. The top level layer that wraps the different Lerc versions is newer. So if this package shows a bug, it is most likely in that layer.
Send an email to [email protected]
Copyright 2015 Esri
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
A local copy of the license and additional notices are located with the source distribution at:
[](Esri Tags: raster, image, encoding, encoded, compression, codec, lerc) [](Esri Language: C++)
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