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Cleanup filters.

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2.0
castano 17 years ago
parent 3359090581
commit 067f3abf54
3 changed files with 93 additions and 249 deletions
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187
src/nvimage/Filter.cpp
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@ -100,6 +100,10 @@ Filter::Filter(float width) : m_width(width)
{
}
/*virtual*/ Filter::~Filter()
{
}
float Filter::sample(float x, float scale, int samples) const
{
// return evaluate(x * scale);
@ -223,11 +227,9 @@ KaiserFilter::KaiserFilter(float w) : Filter(w) { setParameters(4.0f, 1.0f); }
float KaiserFilter::evaluate(float x) const
{
const float sinc_value = sincf(PI * x * stretch);
float t = x / m_width;
if (t * t <= 1.0f)
return sinc_value * bessel0(alpha * sqrtf(1 - t * t)) / bessel0(alpha);
else
return 0;
const float t = x / m_width;
if ((1 - t * t) >= 0) return sinc_value * bessel0(alpha * sqrtf(1 - t * t)) / bessel0(alpha);
else return 0;
}
void KaiserFilter::setParameters(float alpha, float stretch)
@ -239,123 +241,44 @@ void KaiserFilter::setParameters(float alpha, float stretch)
/// Ctor.
Kernel1::Kernel1(uint ws) : m_windowSize(ws)
{
m_data = new float[m_windowSize];
}
/// Copy ctor.
Kernel1::Kernel1(const Kernel1 & k) : m_windowSize(k.m_windowSize)
{
m_data = new float[m_windowSize];
for(uint i = 0; i < m_windowSize; i++) {
m_data[i] = k.m_data[i];
}
}
/// Dtor.
Kernel1::~Kernel1()
{
delete m_data;
}
/// Normalize the filter.
void Kernel1::normalize()
Kernel1::Kernel1(const Filter & f, int iscale, int samples/*= 32*/)
{
float total = 0.0f;
for(uint i = 0; i < m_windowSize; i++) {
total += m_data[i];
}
nvDebugCheck(iscale > 1);
nvDebugCheck(samples > 0);
float inv = 1.0f / total;
for(uint i = 0; i < m_windowSize; i++) {
m_data[i] *= inv;
}
}
#if 0
/// Init 1D filter.
void Kernel1::initFilter(Filter::Enum f, int samples /*= 1*/)
{
nvDebugCheck(f < Filter::Num);
nvDebugCheck(samples >= 1);
const float scale = 1.0f / iscale;
float (* filter_function)(float) = s_filter_array[f].function;
const float support = s_filter_array[f].support;
m_width = f.width() * iscale;
m_windowSize = ceilf(2 * m_width);
m_data = new float[m_windowSize];
const float halfWindowSize = float(m_windowSize) / 2.0f;
const float scale = support / halfWindowSize;
const float offset = float(m_windowSize) / 2;
for(uint i = 0; i < m_windowSize; i++)
float total = 0.0f;
for (int i = 0; i < m_windowSize; i++)
{
m_data[i] = sampleFilter(filter_function, i - halfWindowSize, scale, samples);
const float sample = f.sample(i - offset, scale, samples);
m_data[i] = sample;
total += sample;
}
normalize();
}
/// Init 1D sinc filter.
void Kernel1::initSinc(float stretch /*= 1*/)
{
const float halfWindowSize = float(m_windowSize) / 2;
const float nudge = 0.5f;
for(uint i = 0; i < m_windowSize; i++) {
const float x = (i - halfWindowSize) + nudge;
m_data[i] = sincf(PI * x * stretch);
}
normalize();
}
/// Init 1D Kaiser-windowed sinc filter.
void Kernel1::initKaiser(float alpha /*= 4*/, float stretch /*= 0.5*/, int samples/*= 1*/)
{
const float halfWindowSize = float(m_windowSize) / 2;
const float s_scale = 1.0f / float(samples);
const float x_scale = 1.0f / halfWindowSize;
for(uint i = 0; i < m_windowSize; i++)
const float inv = 1.0f / total;
for (int i = 0; i < m_windowSize; i++)
{
float sum = 0;
for(int s = 0; s < samples; s++)
{
float x = i - halfWindowSize + (s + 0.5f) * s_scale;
const float sinc_value = sincf(PI * x * stretch);
const float window_value = filter_kaiser(x * x_scale, alpha); // @@ should the window be streched? I don't think so.
sum += sinc_value * window_value;
}
m_data[i] = sum;
m_data[i] *= inv;
}
normalize();
}
/// Init 1D Mitchell filter.
void Kernel1::initMitchell(float b, float c)
/// Dtor.
Kernel1::~Kernel1()
{
const float halfWindowSize = float(m_windowSize) / 2;
const float nudge = 0.5f;
for (uint i = 0; i < m_windowSize; i++) {
const float x = (i - halfWindowSize) + nudge;
m_data[i] = filter_mitchell(x / halfWindowSize, b, c);
}
normalize();
delete m_data;
}
#endif
/// Print the kernel for debugging purposes.
void Kernel1::debugPrint()
{
for (uint i = 0; i < m_windowSize; i++) {
for (int i = 0; i < m_windowSize; i++) {
nvDebug("%d: %f\n", i, m_data[i]);
}
}
@ -590,41 +513,13 @@ void Kernel2::initBlendedSobel(const Vector4 & scale)
}
static float frac(float f)
PolyphaseKernel::PolyphaseKernel(const Filter & f, uint srcLength, uint dstLength, int samples/*= 32*/)
{
return f - floorf(f);
}
static bool isMonoPhase(float w)
{
return isZero(frac(w));
}
/*
PolyphaseKernel::PolyphaseKernel(float w, uint l) :
m_width(w),
m_size(ceilf(w) + 1),
m_length(l)
{
// size = width + (length - 1) * phase
m_data = new float[m_size * m_length];
}
PolyphaseKernel::PolyphaseKernel(const PolyphaseKernel & k) :
m_width(k.m_width),
m_size(k.m_size),
m_length(k.m_length)
{
m_data = new float[m_size * m_length];
memcpy(m_data, k.m_data, sizeof(float) * m_size * m_length);
}
*/
PolyphaseKernel::PolyphaseKernel(const Filter & f, uint srcLength, uint dstLength)
{
float scale = float(dstLength) / float(srcLength);
float iscale = 1.0f / scale;
nvCheck(srcLength >= dstLength); // @@ Upsampling not implemented!
nvDebugCheck(samples > 0);
const float scale = float(dstLength) / float(srcLength);
const float iscale = 1.0f / scale;
m_length = dstLength;
m_width = f.width() * iscale;
@ -637,19 +532,19 @@ PolyphaseKernel::PolyphaseKernel(const Filter & f, uint srcLength, uint dstLengt
{
const float center = (0.5f + i) * iscale;
int left = floor(center - m_width);
int right = ceil(center + m_width);
nvCheck(right - left <= (int)m_windowSize);
const int left = floorf(center - m_width);
const int right = ceilf(center + m_width);
nvDebugCheck(right - left <= m_windowSize);
float total = 0.0f;
for (int j = 0; j < m_windowSize; j++)
{
float sample = f.sample(left + j - center, scale, 40);
const float sample = f.sample(left + j - center, scale, samples);
m_data[i * m_windowSize + j] = sample;
total += sample;
}
// normalize weights.
for (int j = 0; j < m_windowSize; j++)
{
@ -670,7 +565,7 @@ void PolyphaseKernel::debugPrint() const
for (uint i = 0; i < m_length; i++)
{
nvDebug("%d: ", i);
for (uint j = 0; j < m_windowSize; j++)
for (int j = 0; j < m_windowSize; j++)
{
nvDebug(" %6.4f", m_data[i * m_windowSize + j]);
}

34
src/nvimage/Filter.h
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@ -4,6 +4,7 @@
#define NV_IMAGE_FILTER_H
#include <nvimage/nvimage.h>
#include <nvcore/Debug.h>
namespace nv
{
@ -14,6 +15,7 @@ namespace nv
{
public:
NVIMAGE_API Filter(float width);
NVIMAGE_API virtual ~Filter();
NVIMAGE_API float width() const { return m_width; }
NVIMAGE_API float sample(float x, float scale, int samples) const;
@ -116,31 +118,29 @@ namespace nv
/// A 1D kernel. Used to precompute filter weights.
class Kernel1
{
NV_FORBID_COPY(Kernel1);
public:
NVIMAGE_API Kernel1(uint windowSize);
NVIMAGE_API Kernel1(const Kernel1 & k);
NVIMAGE_API Kernel1(const Filter & f, int iscale, int samples = 32);
NVIMAGE_API ~Kernel1();
NVIMAGE_API void normalize();
float valueAt(uint x) const {
nvDebugCheck(x < (uint)m_windowSize);
return m_data[x];
}
uint windowSize() const {
int windowSize() const {
return m_windowSize;
}
/*
NVIMAGE_API void initFilter(Filter::Enum filter, int samples = 1);
NVIMAGE_API void initSinc(float stretch = 1);
NVIMAGE_API void initKaiser(float alpha = 4.0f, float stretch = 1.0f, int sampes = 1);
NVIMAGE_API void initMitchell(float b = 1.0f/3.0f, float c = 1.0f/3.0f);
*/
float width() const {
return m_width;
}
NVIMAGE_API void debugPrint();
private:
const uint m_windowSize;
int m_windowSize;
float m_width;
float * m_data;
};
@ -180,12 +180,12 @@ namespace nv
/// A 1D polyphase kernel
class PolyphaseKernel
{
NV_FORBID_COPY(PolyphaseKernel)
NV_FORBID_COPY(PolyphaseKernel);
public:
NVIMAGE_API PolyphaseKernel(const Filter & f, uint srcLength, uint dstLength);
NVIMAGE_API PolyphaseKernel(const Filter & f, uint srcLength, uint dstLength, int samples = 32);
NVIMAGE_API ~PolyphaseKernel();
uint windowSize() const {
int windowSize() const {
return m_windowSize;
}
@ -199,14 +199,14 @@ namespace nv
float valueAt(uint column, uint x) const {
nvDebugCheck(column < m_length);
nvDebugCheck(x < m_windowSize);
nvDebugCheck(x < (uint)m_windowSize);
return m_data[column * m_windowSize + x];
}
NVIMAGE_API void debugPrint() const;
private:
uint m_windowSize;
int m_windowSize;
uint m_length;
float m_width;
float * m_data;

121
src/nvimage/FloatImage.cpp
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@ -599,17 +599,18 @@ FloatImage * FloatImage::downSample(const Filter & filter, WrapMode wm) const
return downSample(filter, w, h, wm);
}
/// Downsample applying a 1D kernel separately in each dimension.
FloatImage * FloatImage::downSample(const Filter & filter, uint w, uint h, WrapMode wm) const
{
// @@ Use monophase filters when frac(m_width / w) == 0
PolyphaseKernel xkernel(filter, m_width, w);
PolyphaseKernel ykernel(filter, m_height, h);
AutoPtr<FloatImage> tmp_image( new FloatImage() );
AutoPtr<FloatImage> dst_image( new FloatImage() );
PolyphaseKernel xkernel(filter, m_width, w, 32);
PolyphaseKernel ykernel(filter, m_height, h, 32);
// @@ Select fastest filtering order:
//if (w * m_height <= h * m_width)
{
@ -748,116 +749,64 @@ float FloatImage::applyKernelHorizontal(const Kernel1 * k, int x, int y, int c,
/// Apply 1D vertical kernel at the given coordinates and return result.
void FloatImage::applyKernelVertical(const PolyphaseKernel & k, int x, int c, WrapMode wm, float * output) const
{
uint length = k.length();
float scale = float(length) / float(m_height);
float iscale = 1.0f / scale;
const uint length = k.length();
const float scale = float(length) / float(m_height);
const float iscale = 1.0f / scale;
float width = k.width();
float windowSize = k.windowSize();
const float width = k.width();
const int windowSize = k.windowSize();
const float * channel = this->channel(c);
for (uint i = 0; i < length; i++)
{
for (uint i = 0; i < length; i++)
{
const float center = (0.5f + i) * iscale;
int left = floor(center - width);
int right = ceil(center + width);
nvCheck(right - left <= windowSize);
float sum = 0;
for (int j = 0; j < windowSize; ++j)
{
const int idx = this->index(x, j+left, wm);
sum += k.valueAt(i, j) * channel[idx];
}
const int left = floor(center - width);
const int right = ceil(center + width);
nvCheck(right - left <= windowSize);
output[i] = sum;
}
/*
const float kernelWidth = k->width();
const float kernelOffset = kernelWidth * 0.5f;
const int kernelLength = k->length();
const int kernelWindow = k->windowSize();
//const float offset = 0.5f * scale * (1 - kw);
const float offset = (0.5f * scale) - kernelOffset;
const float * channel = this->channel(c);
for (int y = 0; y < kernelLength; y++)
{
float sum = 0.0f;
for (int i = 0; i < kernelWindow; i++)
float sum = 0;
for (int j = 0; j < windowSize; ++j)
{
const int src_y = int(y * scale + offset) + i;
const int idx = this->index(x, src_y, wm);
const int idx = this->index(x, j+left, wm);
sum += k->valueAt(y, i) * channel[idx];
sum += k.valueAt(i, j) * channel[idx];
}
output[y] = sum;
output[i] = sum;
}
*/
}
/// Apply 1D horizontal kernel at the given coordinates and return result.
void FloatImage::applyKernelHorizontal(const PolyphaseKernel & k, int y, int c, WrapMode wm, float * output) const
{
uint length = k.length();
float scale = float(length) / float(m_width);
float iscale = 1.0f / scale;
const uint length = k.length();
const float scale = float(length) / float(m_width);
const float iscale = 1.0f / scale;
float width = k.width();
float windowSize = k.windowSize();
const float width = k.width();
const int windowSize = k.windowSize();
const float * channel = this->channel(c);
for (uint i = 0; i < length; i++)
{
for (uint i = 0; i < length; i++)
{
const float center = (0.5f + i) * iscale;
int left = floor(center - width);
int right = ceil(center + width);
nvCheck(right - left <= (int)windowSize);
float sum = 0;
for (int j = 0; j < windowSize; ++j)
{
const int idx = this->index(left + j, y, wm);
sum += k.valueAt(i, j) * channel[idx];
}
const int left = floorf(center - width);
const int right = ceilf(center + width);
nvDebugCheck(right - left <= windowSize);
output[i] = sum;
}
/*
const float kernelWidth = k->width();
const float kernelOffset = kernelWidth * 0.5f;
const int kernelLength = k->length();
const int kernelWindow = k->windowSize();
const float offset = (0.5f * scale) - kernelOffset;
const float * channel = this->channel(c);
for (int x = 0; x < kernelLength; x++)
{
float sum = 0.0f;
for (int e = 0; e < kernelWindow; e++)
float sum = 0;
for (int j = 0; j < windowSize; ++j)
{
const int src_x = int(x * scale + offset) + e;
const int idx = this->index(src_x, y, wm);
const int idx = this->index(left + j, y, wm);
sum += k->valueAt(x, e) * channel[idx];
sum += k.valueAt(i, j) * channel[idx];
}
output[x] = sum;
output[i] = sum;
}
*/
}

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