A universal C++ compression library based on wavelet transformation
- Written in Modern C++
- One-side wavelet decomposition for vectors and matrices
- 5 Daubechies Wavelets DB1-DB5
- Different denoising algorithms
- Fast and efficient compression with MatrixCompressor
- Cross-platform
- CMake >= 3.16
- C++20 compiler
- conan >= 1.56, < 2.0
#include <wavelet_buffer/wavelet_buffer.h>
using drift::Signal1D;
using drift::WaveletBuffer;
using drift::WaveletParameters;
using drift::WaveletTypes;
using DenoiseAlgo = drift::ThresholdAbsDenoiseAlgorithm<float>;
int main() {
Signal1D original = blaze::generate(
1000, [](auto index) { return static_cast<float>(index % 100); });
std::cout << "Original size: " << original.size() * 4 << std::endl;
WaveletBuffer buffer(WaveletParameters{
.signal_shape = {original.size()},
.signal_number = 1,
.decomposition_steps = 3,
.wavelet_type = WaveletTypes::kDB1,
});
// Wavelet decomposition of the signal and denoising
buffer.Decompose(original, DenoiseAlgo(0, 0.3));
// Compress the buffer
std::string arch;
buffer.Serialize(&arch, 16);
std::cout << "Compressed size: " << arch.size() << std::endl;
// Decompress the buffer
auto restored_buffer = WaveletBuffer::Parse(arch);
Signal1D output_signal;
// Restore the signal from wavelet decomposition
restored_buffer->Compose(&output_signal);
std::cout << "Distance between original and restored signal: "
<< blaze::norm(original - output_signal) / original.size()
<< std::endl;
std::cout << "Compression rate: " << original.size() * 4. / arch.size() * 100
<< "%" << std::endl;
}On Ubuntu:
git clone https://github.com/panda-official/WaveletBuffer.git
mkdir build && cd build
cmake -DWB_BUILD_TESTS=ON -DWB_BUILD_BENCHMARKS=ON -DWB_BUILD_EXAMPLES=ON -DCODE_COVERAGE=ON ..
cmake --build . --target install
On MacOS:
git clone https://github.com/panda-official/WaveletBuffer.git
mkdir build && cd build
cmake -DWB_BUILD_TESTS=ON -DWB_BUILD_BENCHMARKS=ON -DWB_BUILD_EXAMPLES=ON -DCODE_COVERAGE=ON ..
cmake --build . --target install
On Windows:
git clone https://github.com/panda-official/WaveletBuffer.git
mkdir build && cd build
cmake -DWB_BUILD_TESTS=ON -DWB_BUILD_BENCHMARKS=ON -DWB_BUILD_EXAMPLES=ON -DCODE_COVERAGE=ON ..
cmake --build . --config Release --target install
find_package(wavelet_buffer REQUIRED)
add_executable(program program.cpp)
target_link_libraries(program wavelet_buffer::wavelet_buffer)
# WaveletBuffer use blaze as linear algebra library which expects you to have a LAPACK library installed
# (it will still work without LAPACK and will not be reduced in functionality, but performance may be limited)
find_package(LAPACK REQUIRED)
target_link_libraries(program ${LAPACK_LIBRARIES})- Documentation
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