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- #include "bsinc_tables.h"
- #include <algorithm>
- #include <array>
- #include <cassert>
- #include <cmath>
- #include <cstddef>
- #include <limits>
- #include <stdexcept>
- #include <vector>
- #include "alnumbers.h"
- #include "alnumeric.h"
- #include "alspan.h"
- #include "bsinc_defs.h"
- #include "opthelpers.h"
- #include "resampler_limits.h"
- namespace {
- using uint = unsigned int;
- /* The zero-order modified Bessel function of the first kind, used for the
- * Kaiser window.
- *
- * I_0(x) = sum_{k=0}^inf (1 / k!)^2 (x / 2)^(2 k)
- * = sum_{k=0}^inf ((x / 2)^k / k!)^2
- *
- * This implementation only handles nu = 0, and isn't the most precise (it
- * starts with the largest value and accumulates successively smaller values,
- * compounding the rounding and precision error), but it's good enough.
- */
- template<typename T, typename U>
- constexpr auto cyl_bessel_i(T nu, U x) -> U
- {
- if(nu != T{0})
- throw std::runtime_error{"cyl_bessel_i: nu != 0"};
- /* Start at k=1 since k=0 is trivial. */
- const double x2{x/2.0};
- double term{1.0};
- double sum{1.0};
- int k{1};
- /* Let the integration converge until the term of the sum is no longer
- * significant.
- */
- double last_sum{};
- do {
- const double y{x2 / k};
- ++k;
- last_sum = sum;
- term *= y * y;
- sum += term;
- } while(sum != last_sum);
- return static_cast<U>(sum);
- }
- /* This is the normalized cardinal sine (sinc) function.
- *
- * sinc(x) = { 1, x = 0
- * { sin(pi x) / (pi x), otherwise.
- */
- constexpr double Sinc(const double x)
- {
- constexpr double epsilon{std::numeric_limits<double>::epsilon()};
- if(!(x > epsilon || x < -epsilon))
- return 1.0;
- return std::sin(al::numbers::pi*x) / (al::numbers::pi*x);
- }
- /* Calculate a Kaiser window from the given beta value and a normalized k
- * [-1, 1].
- *
- * w(k) = { I_0(B sqrt(1 - k^2)) / I_0(B), -1 <= k <= 1
- * { 0, elsewhere.
- *
- * Where k can be calculated as:
- *
- * k = i / l, where -l <= i <= l.
- *
- * or:
- *
- * k = 2 i / M - 1, where 0 <= i <= M.
- */
- constexpr double Kaiser(const double beta, const double k, const double besseli_0_beta)
- {
- if(!(k >= -1.0 && k <= 1.0))
- return 0.0;
- return ::cyl_bessel_i(0, beta * std::sqrt(1.0 - k*k)) / besseli_0_beta;
- }
- /* Calculates the (normalized frequency) transition width of the Kaiser window.
- * Rejection is in dB.
- */
- constexpr double CalcKaiserWidth(const double rejection, const uint order) noexcept
- {
- if(rejection > 21.19)
- return (rejection - 7.95) / (2.285 * al::numbers::pi*2.0 * order);
- /* This enforces a minimum rejection of just above 21.18dB */
- return 5.79 / (al::numbers::pi*2.0 * order);
- }
- /* Calculates the beta value of the Kaiser window. Rejection is in dB. */
- constexpr double CalcKaiserBeta(const double rejection)
- {
- if(rejection > 50.0)
- return 0.1102 * (rejection-8.7);
- if(rejection >= 21.0)
- return (0.5842 * std::pow(rejection-21.0, 0.4)) + (0.07886 * (rejection-21.0));
- return 0.0;
- }
- struct BSincHeader {
- double beta{};
- double scaleBase{};
- double scaleLimit{};
- std::array<double,BSincScaleCount> a{};
- std::array<uint,BSincScaleCount> m{};
- uint total_size{};
- constexpr BSincHeader(uint rejection, uint order, uint maxScale) noexcept
- : beta{CalcKaiserBeta(rejection)}, scaleBase{CalcKaiserWidth(rejection, order) / 2.0}
- , scaleLimit{1.0 / maxScale}
- {
- const auto base_a = (order+1.0) / 2.0;
- for(uint si{0};si < BSincScaleCount;++si)
- {
- const auto scale = lerpd(scaleBase, 1.0, (si+1u) / double{BSincScaleCount});
- a[si] = std::min(base_a/scale, base_a*maxScale);
- /* std::ceil() isn't constexpr until C++23, this should behave the
- * same.
- */
- auto a_ = static_cast<uint>(a[si]);
- a_ += (static_cast<double>(a_) != a[si]);
- m[si] = a_ * 2u;
- total_size += 4u * BSincPhaseCount * ((m[si]+3u) & ~3u);
- }
- }
- };
- /* 11th and 23rd order filters (12 and 24-point respectively) with a 60dB drop
- * at nyquist. Each filter will scale up to double size when downsampling, to
- * 23rd and 47th order respectively.
- */
- constexpr auto bsinc12_hdr = BSincHeader{60, 11, 2};
- constexpr auto bsinc24_hdr = BSincHeader{60, 23, 2};
- /* 47th order filter (48-point) with an 80dB drop at nyquist. The filter order
- * doesn't increase when downsampling.
- */
- constexpr auto bsinc48_hdr = BSincHeader{80, 47, 1};
- template<const BSincHeader &hdr>
- struct SIMDALIGN BSincFilterArray {
- alignas(16) std::array<float, hdr.total_size> mTable{};
- BSincFilterArray()
- {
- static constexpr auto BSincPointsMax = (hdr.m[0]+3u) & ~3u;
- static_assert(BSincPointsMax <= MaxResamplerPadding, "MaxResamplerPadding is too small");
- using filter_type = std::array<std::array<double,BSincPointsMax>,BSincPhaseCount>;
- auto filter = std::vector<filter_type>(BSincScaleCount);
- static constexpr auto besseli_0_beta = ::cyl_bessel_i(0, hdr.beta);
- /* Calculate the Kaiser-windowed Sinc filter coefficients for each
- * scale and phase index.
- */
- for(uint si{0};si < BSincScaleCount;++si)
- {
- const auto a = hdr.a[si];
- const auto m = hdr.m[si];
- const auto l = std::floor(m*0.5) - 1.0;
- const auto o = size_t{BSincPointsMax-m} / 2u;
- const auto scale = lerpd(hdr.scaleBase, 1.0, (si+1u) / double{BSincScaleCount});
- /* Calculate an appropriate cutoff frequency. An explanation may be
- * in order here.
- *
- * When up-sampling, or down-sampling by less than the max scaling
- * factor (when scale >= scaleLimit), the filter order increases as
- * the down-sampling factor is reduced, enabling a consistent
- * filter response output.
- *
- * When down-sampling by more than the max scale factor, the filter
- * order stays constant to avoid further increasing the processing
- * cost, causing the transition width to increase. This would
- * normally be compensated for by reducing the cutoff frequency,
- * to keep the transition band under the nyquist frequency and
- * avoid aliasing. However, this has the side-effect of attenuating
- * more of the original high frequency content, which can be
- * significant with more extreme down-sampling scales.
- *
- * To combat this, we can allow for some aliasing to keep the
- * cutoff frequency higher than it would otherwise be. We can allow
- * the transition band to "wrap around" the nyquist frequency, so
- * the output would have some low-level aliasing that overlays with
- * the attenuated frequencies in the transition band. This allows
- * the cutoff frequency to remain fixed as the transition width
- * increases, until the stop frequency aliases back to the cutoff
- * frequency and the transition band becomes fully wrapped over
- * itself, at which point the cutoff frequency will lower at half
- * the rate the transition width increases.
- *
- * This has an additional benefit when dealing with typical output
- * rates like 44 or 48khz. Since human hearing maxes out at 20khz,
- * and these rates handle frequencies up to 22 or 24khz, this lets
- * some aliasing get masked. For example, the bsinc24 filter with
- * 48khz output has a cutoff of 20khz when down-sampling, and a
- * 4khz transition band. When down-sampling by more extreme scales,
- * the cutoff frequency can stay at 20khz while the transition
- * width doubles before any aliasing noise may become audible.
- *
- * This is what we do here.
- *
- * 'max_cutoff` is the upper bound normalized cutoff frequency for
- * this scale factor, that aligns with the same absolute frequency
- * as nominal resample factors. When up-sampling (scale == 1), the
- * cutoff can't be raised further than this, or else it would
- * prematurely add audible aliasing noise.
- *
- * 'width' is the normalized transition width for this scale
- * factor.
- *
- * '(scale - width)*0.5' calculates the cutoff frequency necessary
- * for the transition band to fully wrap on itself around the
- * nyquist frequency. If this is larger than max_cutoff, the
- * transition band is not fully wrapped at this scale and the
- * cutoff doesn't need adjustment.
- */
- const auto max_cutoff = (0.5 - hdr.scaleBase)*scale;
- const auto width = hdr.scaleBase * std::max(hdr.scaleLimit, scale);
- const auto cutoff2 = std::min(max_cutoff, (scale - width)*0.5) * 2.0;
- for(uint pi{0};pi < BSincPhaseCount;++pi)
- {
- const auto phase = l + (pi/double{BSincPhaseCount});
- for(uint i{0};i < m;++i)
- {
- const auto x = static_cast<double>(i) - phase;
- filter[si][pi][o+i] = Kaiser(hdr.beta, x/a, besseli_0_beta) * cutoff2 *
- Sinc(cutoff2*x);
- }
- }
- }
- size_t idx{0};
- for(size_t si{0};si < BSincScaleCount;++si)
- {
- const auto m = (hdr.m[si]+3_uz) & ~3_uz;
- const auto o = size_t{BSincPointsMax-m} / 2u;
- /* Write out each phase index's filter and phase delta for this
- * quality scale.
- */
- for(size_t pi{0};pi < BSincPhaseCount;++pi)
- {
- for(size_t i{0};i < m;++i)
- mTable[idx++] = static_cast<float>(filter[si][pi][o+i]);
- /* Linear interpolation between phases is simplified by pre-
- * calculating the delta (b - a) in: x = a + f (b - a)
- */
- if(pi < BSincPhaseCount-1)
- {
- for(size_t i{0};i < m;++i)
- {
- const double phDelta{filter[si][pi+1][o+i] - filter[si][pi][o+i]};
- mTable[idx++] = static_cast<float>(phDelta);
- }
- }
- else
- {
- /* The delta target for the last phase index is the first
- * phase index with the coefficients offset by one. The
- * first delta targets 0, as it represents a coefficient
- * for a sample that won't be part of the filter.
- */
- mTable[idx++] = static_cast<float>(0.0 - filter[si][pi][o]);
- for(size_t i{1};i < m;++i)
- {
- const double phDelta{filter[si][0][o+i-1] - filter[si][pi][o+i]};
- mTable[idx++] = static_cast<float>(phDelta);
- }
- }
- }
- /* Now write out each phase index's scale and phase+scale deltas,
- * to complete the bilinear equation for the combination of phase
- * and scale.
- */
- if(si < BSincScaleCount-1)
- {
- for(size_t pi{0};pi < BSincPhaseCount;++pi)
- {
- for(size_t i{0};i < m;++i)
- {
- const double scDelta{filter[si+1][pi][o+i] - filter[si][pi][o+i]};
- mTable[idx++] = static_cast<float>(scDelta);
- }
- if(pi < BSincPhaseCount-1)
- {
- for(size_t i{0};i < m;++i)
- {
- const double spDelta{(filter[si+1][pi+1][o+i]-filter[si+1][pi][o+i]) -
- (filter[si][pi+1][o+i]-filter[si][pi][o+i])};
- mTable[idx++] = static_cast<float>(spDelta);
- }
- }
- else
- {
- mTable[idx++] = static_cast<float>((0.0 - filter[si+1][pi][o]) -
- (0.0 - filter[si][pi][o]));
- for(size_t i{1};i < m;++i)
- {
- const double spDelta{(filter[si+1][0][o+i-1] - filter[si+1][pi][o+i]) -
- (filter[si][0][o+i-1] - filter[si][pi][o+i])};
- mTable[idx++] = static_cast<float>(spDelta);
- }
- }
- }
- }
- else
- {
- /* The last scale index doesn't have scale-related deltas. */
- for(size_t i{0};i < BSincPhaseCount*m*2;++i)
- mTable[idx++] = 0.0f;
- }
- }
- assert(idx == hdr.total_size);
- }
- [[nodiscard]] constexpr auto getHeader() const noexcept -> const BSincHeader& { return hdr; }
- [[nodiscard]] constexpr auto getTable() const noexcept { return al::span{mTable}; }
- };
- const auto bsinc12_filter = BSincFilterArray<bsinc12_hdr>{};
- const auto bsinc24_filter = BSincFilterArray<bsinc24_hdr>{};
- const auto bsinc48_filter = BSincFilterArray<bsinc48_hdr>{};
- template<typename T>
- constexpr BSincTable GenerateBSincTable(const T &filter)
- {
- BSincTable ret{};
- const BSincHeader &hdr = filter.getHeader();
- ret.scaleBase = static_cast<float>(hdr.scaleBase);
- ret.scaleRange = static_cast<float>(1.0 / (1.0 - hdr.scaleBase));
- for(size_t i{0};i < BSincScaleCount;++i)
- ret.m[i] = (hdr.m[i]+3u) & ~3u;
- ret.filterOffset[0] = 0;
- for(size_t i{1};i < BSincScaleCount;++i)
- ret.filterOffset[i] = ret.filterOffset[i-1] + ret.m[i-1]*4*BSincPhaseCount;
- ret.Tab = filter.getTable();
- return ret;
- }
- } // namespace
- const BSincTable gBSinc12{GenerateBSincTable(bsinc12_filter)};
- const BSincTable gBSinc24{GenerateBSincTable(bsinc24_filter)};
- const BSincTable gBSinc48{GenerateBSincTable(bsinc48_filter)};
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