11#include <memory_resource>
12#include <nk/value/value.hpp>
15namespace nk::wavelet {
41 std::pmr::memory_resource *mr =
nullptr);
58 std::pmr::memory_resource *mr =
nullptr);
86 std::pmr::memory_resource *mr =
nullptr);
106 std::pmr::memory_resource *mr =
nullptr);
135 const Value &x, std::pmr::memory_resource *mr =
nullptr);
Core MATLAB-compatible multidimensional array and scalar value type.
Value wnoisest(const Value &C, const Value &L, const Value &S, std::pmr::memory_resource *mr=nullptr)
Per-level noise σ estimate (σ = wnoisest(C, L, S)).
Value wdenoise(const Value &x, int level, const std::string &wname, std::pmr::memory_resource *mr=nullptr)
VisuShrink-style soft-threshold denoising (y = wdenoise(x, level, wname)).
DdencmpResult ddencmp(const std::string &opt, const std::string &type, const Value &x, std::pmr::memory_resource *mr=nullptr)
Default threshold / settings for wavelet denoising or compression.
Value wentropy(const Value &X, const std::string &type, double param=0.0, std::pmr::memory_resource *mr=nullptr)
Entropy of a coefficient vector (E = wentropy(X, T[, P])).
Value wthresh(const Value &X, const std::string &sorh, double T, std::pmr::memory_resource *mr=nullptr)
Element-wise wavelet coefficient thresholding (Y = wthresh(X, sorh, T)).
Default denoising / compression parameters ([thr, sorh, keepapp] = ddencmp(opt, type,...
Value keepapp
Keep approximation flag (always 1).
Value sorh
Soft ('s') or hard ('h') thresholding.