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2025-05-03 12:51:37 -03:00

372 lines
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C++

#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)};