From 8be3692ca6ed4d1033d6f3210ffc87fe528d0a47 Mon Sep 17 00:00:00 2001
From: Wenzel Jakob <wenzel@inf.ethz.ch>
Date: Fri, 6 Jun 2014 01:55:02 +0200
Subject: [PATCH] further filtering/resampling code improvements

---
 include/mitsuba/core/bitmap.h  |  69 ++++--
 include/mitsuba/core/rfilter.h | 371 +++++++++++++++++++++------------
 include/mitsuba/core/util.h    |   4 +-
 include/mitsuba/render/shape.h |   2 +-
 src/libcore/bitmap.cpp         |  27 ++-
 src/libpython/base.h           |  10 +-
 src/libpython/core.cpp         |  25 ++-
 src/rfilters/box.cpp           |   2 +-
 8 files changed, 335 insertions(+), 175 deletions(-)

diff --git a/include/mitsuba/core/bitmap.h b/include/mitsuba/core/bitmap.h
index 3b64bb25..9384ff33 100644
--- a/include/mitsuba/core/bitmap.h
+++ b/include/mitsuba/core/bitmap.h
@@ -1023,9 +1023,9 @@ public:
 	 * horizontal and vertical boundary conditions when looking up data
 	 * outside of the input domain.
 	 *
-	 * A maximum and maximum image value can be specified to prevent to prevent
-	 * out-of-range values that are created by the resampling process.
-	 * 
+	 * A maximum and maximum image value can be specified to prevent to
+	 * prevent out-of-range values that are created by the resampling process.
+	 *
 	 * The optional 'temp' parameter can be used to pass an image of
 	 * resolution <tt>Vector2i(target->getWidth(), this->getHeight())</tt>
 	 * to avoid intermediate memory allocations.
@@ -1036,25 +1036,6 @@ public:
 		Bitmap *target, Bitmap *temp = NULL,
 		Float minValue = 0.0f, Float maxValue = 1.0f) const;
 
-	/**
-	 * \brief Apply a separable filter to the image
-	 *
-	 * Applies the provided filter while observing the specified
-	 * horizontal and vertical boundary conditions when looking up data
-	 * outside of the input domain.
-	 *
-	 * A maximum and maximum image value can be specified to prevent to prevent
-	 * out-of-range values that are created by the filtering process.
-	 * 
-	 * The optional 'temp' parameter can be used to pass an image of
-	 * the same dimensions as the source and target image.
-	 */
-	void filter(const ReconstructionFilter *rfilter,
-		ReconstructionFilter::EBoundaryCondition bch,
-		ReconstructionFilter::EBoundaryCondition bcv,
-		Bitmap *target, Bitmap *temp = NULL,
-		Float minValue = 0.0f, Float maxValue = 1.0f) const;
-
 	/**
 	 * \brief Up- or down-sample this image to a different resolution
 	 *
@@ -1064,6 +1045,8 @@ public:
 	 *
 	 * A maximum and maximum image value can be specified to prevent to prevent
 	 * out-of-range values that are created by the resampling process.
+	 *
+	 * This function allocates a new output image and returns it.
 	 */
 	ref<Bitmap> resample(const ReconstructionFilter *rfilter,
 		ReconstructionFilter::EBoundaryCondition bch,
@@ -1071,6 +1054,48 @@ public:
 		const Vector2i &size, Float minValue = 0.0f,
 		Float maxValue = 1.0f) const;
 
+	/**
+	 * \brief Apply a separable convolution filter to the image
+	 *
+	 * Applies the provided filter while observing the specified
+	 * horizontal and vertical boundary conditions when looking up data
+	 * outside of the input domain.
+	 *
+	 * In comparison to \ref convolve(), this function operates
+	 * in the primal domain.
+	 *
+	 * A maximum and maximum image value can be specified to prevent to
+	 * prevent out-of-range values that are created by the filtering process.
+	 *
+	 * The optional 'temp' parameter can be used to pass an image of
+	 * the same dimensions as the source and target image.
+	 */
+	void filter(const ReconstructionFilter *rfilter,
+		ReconstructionFilter::EBoundaryCondition bch,
+		ReconstructionFilter::EBoundaryCondition bcv,
+		Bitmap *target, Bitmap *temp = NULL,
+		Float minValue = 0.0f, Float maxValue = 1.0f) const;
+
+	/**
+	 * \brief Apply a separable convolution filter to the image
+	 *
+	 * Applies the provided filter while observing the specified
+	 * horizontal and vertical boundary conditions when looking up data
+	 * outside of the input domain.
+	 *
+	 * In comparison to \ref convolve(), this function operates
+	 * in the primal domain.
+	 *
+	 * A maximum and maximum image value can be specified to prevent to
+	 * prevent out-of-range values that are created by the filtering process.
+	 *
+	 * This function allocates a new output image and returns it.
+	 */
+	ref<Bitmap> filter(const ReconstructionFilter *rfilter,
+		ReconstructionFilter::EBoundaryCondition bch,
+		ReconstructionFilter::EBoundaryCondition bcv,
+		Float minValue = 0.0f, Float maxValue = 1.0f) const;
+
 	//! @}
 	// ======================================================================
 
diff --git a/include/mitsuba/core/rfilter.h b/include/mitsuba/core/rfilter.h
index 186d71cd..81e3617d 100644
--- a/include/mitsuba/core/rfilter.h
+++ b/include/mitsuba/core/rfilter.h
@@ -84,8 +84,8 @@ public:
 
 	MTS_DECLARE_CLASS()
 protected:
-    /// Create a new reconstruction filter
-    ReconstructionFilter(const Properties &props);
+	/// Create a new reconstruction filter
+	ReconstructionFilter(const Properties &props);
 
 	/// Unserialize a filter
 	ReconstructionFilter(Stream *stream, InstanceManager *manager);
@@ -121,126 +121,88 @@ template <typename Scalar> struct Resampler {
 	 *      outside of the defined input domain.
 	 */
 	Resampler(const ReconstructionFilter *rfilter, ReconstructionFilter::EBoundaryCondition bc,
-			int sourceRes, int targetRes) : m_bc(bc), m_sourceRes(sourceRes), m_targetRes(targetRes) {
+			int sourceRes, int targetRes) : m_bc(bc), m_sourceRes(sourceRes), m_targetRes(targetRes),
+			m_start(NULL), m_weights(NULL) {
 		SAssert(sourceRes > 0 && targetRes > 0);
 		Float filterRadius = rfilter->getRadius(), scale = 1.0f, invScale = 1.0f;
 
 		/* Low-pass filter: scale reconstruction filters when downsampling */
 		if (targetRes < sourceRes) {
 			scale = (Float) sourceRes / (Float) targetRes;
-		    invScale = 1 / scale;
+			invScale = 1 / scale;
 			filterRadius *= scale;
 		}
 
-		m_taps = floorToInt(filterRadius * 2);
-		m_start = new int[targetRes];
-		m_weights = new Scalar[m_taps * targetRes];
-		m_fastStart = 0;
-		m_fastEnd = m_targetRes;
+		m_taps = ceilToInt(filterRadius * 2);
+		if (sourceRes == targetRes && (m_taps % 2) != 1)
+			--m_taps;
+		m_halfTaps = m_taps / 2;
 
-		for (int i=0; i<targetRes; i++) {
-			/* Compute the fractional coordinates of the new sample i in the original coordinates */
-			Float center = (i + (Float) 0.5f) / targetRes * sourceRes;
+		if (sourceRes != targetRes) { /* Resampling mode */
+			m_start = new int[targetRes];
+			m_weights = new Scalar[m_taps * targetRes];
+			m_fastStart = 0;
+			m_fastEnd = m_targetRes;
 
-			/* Determine the index of the first original sample that might contribute */
-			m_start[i] = floorToInt(center - filterRadius + (Float) 0.5f);
+			for (int i=0; i<targetRes; i++) {
+				/* Compute the fractional coordinates of the new sample i in the original coordinates */
+				Float center = (i + (Float) 0.5f) / targetRes * sourceRes;
 
-			/* Determine the size of center region, on which to run fast non condition-aware code */
-			if (m_start[i] < 0)
-				m_fastStart = std::max(m_fastStart, i + 1);
-			else if (m_start[i] + m_taps - 1 >= m_sourceRes)
-				m_fastEnd = std::min(m_fastEnd, i - 1);
+				/* Determine the index of the first original sample that might contribute */
+				m_start[i] = floorToInt(center - filterRadius + (Float) 0.5f);
 
+				/* Determine the size of center region, on which to run fast non condition-aware code */
+				if (m_start[i] < 0)
+					m_fastStart = std::max(m_fastStart, i + 1);
+				else if (m_start[i] + m_taps - 1 >= m_sourceRes)
+					m_fastEnd = std::min(m_fastEnd, i - 1);
+
+				Float sum = 0;
+				for (int j=0; j<m_taps; j++) {
+					/* Compute the the position where the filter should be evaluated */
+					Float pos = m_start[i] + j + (Float) 0.5f - center;
+
+					/* Perform the evaluation and record the weight */
+					Float weight = rfilter->eval(pos * invScale);
+					m_weights[i * m_taps + j] = (Scalar) weight;
+					sum += weight;
+				}
+
+				/* Normalize the contribution of each sample */
+				Float normalization = 1.0f / sum;
+				for (int j=0; j<m_taps; j++) {
+					Scalar &value = m_weights[i * m_taps + j];
+					value = (Scalar) ((Float) value * normalization);
+				}
+			}
+		} else { /* Filtering mode */
+			m_weights = new Scalar[m_taps];
 			Float sum = 0;
-			for (int j=0; j<m_taps; j++) {
-				/* Compute the the position where the filter should be evaluated */
-				Float pos = m_start[i] + j + (Float) 0.5f - center;
-
-				/* Perform the evaluation and record the weight */
-				Float weight = rfilter->eval(pos * invScale);
-				m_weights[i * m_taps + j] = (Scalar) weight;
+			for (int i=0; i<m_taps; i++) {
+				Float weight = (Scalar) rfilter->eval((Float) (i-m_halfTaps));
+				m_weights[i] = weight;
 				sum += weight;
 			}
-
-			/* Normalize the contribution of each sample */
 			Float normalization = 1.0f / sum;
-			for (int j=0; j<m_taps; j++) {
-				Scalar &value = m_weights[i * m_taps + j];
+			for (int i=0; i<m_taps; i++) {
+				Scalar &value = m_weights[i];
 				value = (Scalar) ((Float) value * normalization);
 			}
+			m_fastStart = std::min(m_halfTaps, m_targetRes-1);
+			m_fastEnd = std::max(m_targetRes-m_halfTaps-1, 0);
 		}
+
+		/* Don't have overlapping fast start/end intervals when
+		   the target image is very small compared to the source image */
 		m_fastStart = std::min(m_fastStart, m_fastEnd);
 	}
 
 	/// Release all memory
 	~Resampler() {
-		delete[] m_start;
-		delete[] m_weights;
-	}
-
-	/**
-	 * \brief Resample a multi-channel array
-	 *
-	 * \param source
-	 *     Source array of samples
-	 * \param target
-	 *     Target array of samples
-	 * \param sourceStride
-	 *     Stride of samples in the source array. A value
-	 *     of '1' implies that they are densely packed.
-	 * \param targetStride
-	 *     Stride of samples in the source array. A value
-	 *     of '1' implies that they are densely packed.
-	 * \param channels
-	 *     Number of channels to be resampled
-	 */
-	void resample(const Scalar *source, size_t sourceStride,
-			Scalar *target, size_t targetStride, int channels) {
-		const int taps = m_taps;
-		targetStride = channels * (targetStride - 1);
-		sourceStride *= channels;
-
-		/* Resample the left border region, while accounting for the boundary conditions */
-		for (int i=0; i<m_fastStart; ++i) {
-			int start = m_start[i];
-
-			for (int ch=0; ch<channels; ++ch) {
-				Scalar result = 0;
-				for (int j=0; j<taps; ++j)
-					result += lookup(source, start + j, sourceStride, ch) * m_weights[i * taps + j];
-				*target++ = result;
-			}
-
-			target += targetStride;
-		}
-
-		/* Use a faster, vectorizable loop for resampling the main portion */
-		for (int i=m_fastStart; i<m_fastEnd; ++i) {
-			int start = m_start[i];
-
-			for (int ch=0; ch<channels; ++ch) {
-				Scalar result = 0;
-				for (int j=0; j<taps; ++j)
-					result += source[sourceStride * (start + j) + ch] * m_weights[i * taps + j];
-				*target++ = result;
-			}
-
-			target += targetStride;
-		}
-
-		/* Resample the right border region, while accounting for the boundary conditions */
-		for (int i=m_fastEnd; i<m_targetRes; ++i) {
-			int start = m_start[i];
-
-			for (int ch=0; ch<channels; ++ch) {
-				Scalar result = 0;
-				for (int j=0; j<taps; ++j)
-					result += lookup(source, start + j, sourceStride, ch) * m_weights[i * taps + j];
-				*target++ = result;
-			}
-
-			target += targetStride;
-		}
+		if (m_start)
+			delete[] m_start;
+		if (m_weights)
+			delete[] m_weights;
 	}
 
 	/**
@@ -270,53 +232,206 @@ template <typename Scalar> struct Resampler {
 	void resampleAndClamp(const Scalar *source, size_t sourceStride,
 			Scalar *target, size_t targetStride, int channels,
 			Scalar min = (Scalar) 0, Scalar max = (Scalar) 1) {
-		const int taps = m_taps;
+		const int taps = m_taps, halfTaps = m_halfTaps;
 		targetStride = channels * (targetStride - 1);
 		sourceStride *= channels;
 
-		/* Resample the left border region, while accounting for the boundary conditions */
-		for (int i=0; i<m_fastStart; ++i) {
-			int start = m_start[i];
+		if (m_start) {
+			/* Resample the left border region, while accounting for the boundary conditions */
+			for (int i=0; i<m_fastStart; ++i) {
+				int start = m_start[i];
 
-			for (int ch=0; ch<channels; ++ch) {
-				Scalar result = 0;
-				for (int j=0; j<taps; ++j)
-					result += lookup(source, start + j, sourceStride, ch) * m_weights[i * taps + j];
-				*target++ = std::min(max, std::max(min, result));
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += lookup(source, start + j, sourceStride, ch) * m_weights[i * taps + j];
+				    *target++ = std::min(max, std::max(min, result));
+				}
+
+				target += targetStride;
 			}
 
-			target += targetStride;
-		}
+			/* Use a faster, vectorizable loop for resampling the main portion */
+			for (int i=m_fastStart; i<m_fastEnd; ++i) {
+				int start = m_start[i];
 
-		/* Use a faster, vectorizable loop for resampling the main portion */
-		for (int i=m_fastStart; i<m_fastEnd; ++i) {
-			int start = m_start[i];
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += source[sourceStride * (start + j) + ch] * m_weights[i * taps + j];
+				    *target++ = std::min(max, std::max(min, result));
+				}
 
-			for (int ch=0; ch<channels; ++ch) {
-				Scalar result = 0;
-				for (int j=0; j<taps; ++j)
-					result += source[sourceStride * (start + j) + ch] * m_weights[i * taps + j];
-				*target++ = std::min(max, std::max(min, result));
+				target += targetStride;
 			}
 
-			target += targetStride;
-		}
+			/* Resample the right border region, while accounting for the boundary conditions */
+			for (int i=m_fastEnd; i<m_targetRes; ++i) {
+				int start = m_start[i];
 
-		/* Resample the right border region, while accounting for the boundary conditions */
-		for (int i=m_fastEnd; i<m_targetRes; ++i) {
-			int start = m_start[i];
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += lookup(source, start + j, sourceStride, ch) * m_weights[i * taps + j];
+				    *target++ = std::min(max, std::max(min, result));
+				}
 
-			for (int ch=0; ch<channels; ++ch) {
-				Scalar result = 0;
-				for (int j=0; j<taps; ++j)
-					result += lookup(source, start + j, sourceStride, ch) * m_weights[i * taps + j];
-				*target++ = std::min(max, std::max(min, result));
+				target += targetStride;
+			}
+		} else {
+			/* Filter the left border region, while accounting for the boundary conditions */
+			for (int i=0; i<m_fastStart; ++i) {
+				int start = i - halfTaps;
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += lookup(source, start + j, sourceStride, ch) * m_weights[j];
+				    *target++ = std::min(max, std::max(min, result));
+				}
+
+				target += targetStride;
 			}
 
-			target += targetStride;
+			/* Use a faster, vectorizable loop for filtering the main portion */
+			for (int i=m_fastStart; i<m_fastEnd; ++i) {
+				int start = i - halfTaps;
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += source[sourceStride * (start + j) + ch] * m_weights[j];
+				    *target++ = std::min(max, std::max(min, result));
+				}
+
+				target += targetStride;
+			}
+
+			/* Filter the right border region, while accounting for the boundary conditions */
+			for (int i=m_fastEnd; i<m_targetRes; ++i) {
+				int start = i - halfTaps;
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += lookup(source, start + j, sourceStride, ch) * m_weights[j];
+				    *target++ = std::min(max, std::max(min, result));
+				}
+
+				target += targetStride;
+			}
 		}
 	}
 
+	/**
+	 * \brief Resample a multi-channel array
+	 *
+	 * \param source
+	 *     Source array of samples
+	 * \param target
+	 *     Target array of samples
+	 * \param sourceStride
+	 *     Stride of samples in the source array. A value
+	 *     of '1' implies that they are densely packed.
+	 * \param targetStride
+	 *     Stride of samples in the source array. A value
+	 *     of '1' implies that they are densely packed.
+	 * \param channels
+	 *     Number of channels to be resampled
+	 */
+	void resample(const Scalar *source, size_t sourceStride,
+			Scalar *target, size_t targetStride, int channels) {
+		const int taps = m_taps, halfTaps = m_halfTaps;
+
+		targetStride = channels * (targetStride - 1);
+		sourceStride *= channels;
+
+		if (m_start) {
+			/* Resample the left border region, while accounting for the boundary conditions */
+			for (int i=0; i<m_fastStart; ++i) {
+				int start = m_start[i];
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += lookup(source, start + j, sourceStride, ch) * m_weights[i * taps + j];
+					*target++ = result;
+				}
+
+				target += targetStride;
+			}
+
+			/* Use a faster, vectorizable loop for resampling the main portion */
+			for (int i=m_fastStart; i<m_fastEnd; ++i) {
+				int start = m_start[i];
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += source[sourceStride * (start + j) + ch] * m_weights[i * taps + j];
+					*target++ = result;
+				}
+
+				target += targetStride;
+			}
+
+			/* Resample the right border region, while accounting for the boundary conditions */
+			for (int i=m_fastEnd; i<m_targetRes; ++i) {
+				int start = m_start[i];
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += lookup(source, start + j, sourceStride, ch) * m_weights[i * taps + j];
+					*target++ = result;
+				}
+
+				target += targetStride;
+			}
+		} else {
+			/* Filter the left border region, while accounting for the boundary conditions */
+			for (int i=0; i<m_fastStart; ++i) {
+				int start = i - halfTaps;
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += lookup(source, start + j, sourceStride, ch) * m_weights[j];
+					*target++ = result;
+				}
+
+				target += targetStride;
+			}
+
+			/* Use a faster, vectorizable loop for filtering the main portion */
+			for (int i=m_fastStart; i<m_fastEnd; ++i) {
+				int start = i - halfTaps;
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += source[sourceStride * (start + j) + ch] * m_weights[j];
+					*target++ = result;
+				}
+
+				target += targetStride;
+			}
+
+			/* Filter the right border region, while accounting for the boundary conditions */
+			for (int i=m_fastEnd; i<m_targetRes; ++i) {
+				int start = i - halfTaps;
+
+				for (int ch=0; ch<channels; ++ch) {
+					Scalar result = 0;
+					for (int j=0; j<taps; ++j)
+						result += lookup(source, start + j, sourceStride, ch) * m_weights[j];
+					*target++ = result;
+				}
+
+				target += targetStride;
+			}
+		}
+	}
 
 private:
 	FINLINE Scalar lookup(const Scalar *source, int pos, size_t stride, int offset) const {
@@ -349,7 +464,7 @@ private:
 	int *m_start;
 	Scalar *m_weights;
 	int m_fastStart, m_fastEnd;
-	int m_taps;
+	int m_taps, m_halfTaps;
 };
 
 extern MTS_EXPORT_CORE std::ostream &operator<<(std::ostream &os, const ReconstructionFilter::EBoundaryCondition &value);
diff --git a/include/mitsuba/core/util.h b/include/mitsuba/core/util.h
index f138e7cb..621d5673 100644
--- a/include/mitsuba/core/util.h
+++ b/include/mitsuba/core/util.h
@@ -51,8 +51,8 @@ extern MTS_EXPORT_CORE std::string indent(const std::string &string, int amount=
 extern MTS_EXPORT_CORE std::string formatString(const char *pFmt, ...);
 
 /**
- * \brief Convert a time difference (in ms) to a string representation
- * \param time Time value in milliseconds
+ * \brief Convert a time difference (in seconds) to a string representation
+ * \param time Time difference in (fractional) sections
  * \param precise When set to true, a higher-precision string representation
  * is generated.
  */
diff --git a/include/mitsuba/render/shape.h b/include/mitsuba/render/shape.h
index 65e2587d..d0013b4e 100644
--- a/include/mitsuba/render/shape.h
+++ b/include/mitsuba/render/shape.h
@@ -121,7 +121,7 @@ public:
 	/// Move the intersection forward or backward through time
 	inline void adjustTime(Float time);
 
-	/// Calls the suitable implementaiton of \ref Shape::getNormalDerivative()
+	/// Calls the suitable implementation of \ref Shape::getNormalDerivative()
 	inline void getNormalDerivative(Vector &dndu, Vector &dndv,
 		bool shadingFrame = true) const;
 
diff --git a/src/libcore/bitmap.cpp b/src/libcore/bitmap.cpp
index 93944591..81acd5ea 100644
--- a/src/libcore/bitmap.cpp
+++ b/src/libcore/bitmap.cpp
@@ -23,6 +23,7 @@
 #include <boost/algorithm/string.hpp>
 #include <boost/scoped_array.hpp>
 #include <boost/thread/mutex.hpp>
+#include <set>
 
 #if defined(__WINDOWS__)
 #undef _CRT_SECURE_NO_WARNINGS
@@ -2216,12 +2217,12 @@ void Bitmap::applyMatrix(Float matrix_[3][3]) {
 	}
 }
 
-/// Bitmap resampling utility function
+/// Bitmap filtering / resampling utility function
 template <typename Scalar> static void resample(ref<const ReconstructionFilter> rfilter,
 	ReconstructionFilter::EBoundaryCondition bch,
 	ReconstructionFilter::EBoundaryCondition bcv,
 	const Bitmap *source, Bitmap *target, ref<Bitmap> temp, Float minValue,
-	Float maxValue, bool forceFiltering) {
+	Float maxValue, bool filter) {
 
 	if (!rfilter) {
 		/* Resample using a 2-lobed Lanczos reconstruction filter */
@@ -2235,7 +2236,7 @@ template <typename Scalar> static void resample(ref<const ReconstructionFilter>
 	}
 
 	if (source->getHeight() == target->getHeight() &&
-		source->getWidth() == target->getWidth() && !forceFiltering) {
+		source->getWidth() == target->getWidth() && !filter) {
 		memcpy(target->getData(), source->getData(), source->getBufferSize());
 		return;
 	}
@@ -2245,13 +2246,13 @@ template <typename Scalar> static void resample(ref<const ReconstructionFilter>
 		minValue != -std::numeric_limits<Float>::infinity() ||
 		maxValue !=  std::numeric_limits<Float>::infinity();
 
-	if (source->getWidth() != target->getWidth() || forceFiltering) {
+	if (source->getWidth() != target->getWidth() || filter) {
 		/* Re-sample along the X direction */
 		Resampler<Scalar> r(rfilter, bch, source->getWidth(), target->getWidth());
 
 		/* Create a bitmap for intermediate storage */
 		if (!temp) {
-			if (source->getHeight() == target->getHeight() && !forceFiltering)
+			if (source->getHeight() == target->getHeight() && !filter)
 				temp = target; // write directly to the output bitmap
 			else // otherwise: write to a temporary bitmap
 				temp = new Bitmap(source->getPixelFormat(), source->getComponentFormat(),
@@ -2289,7 +2290,7 @@ template <typename Scalar> static void resample(ref<const ReconstructionFilter>
 		source = temp;
 	}
 
-	if (source->getHeight() != target->getHeight() || forceFiltering) {
+	if (source->getHeight() != target->getHeight() || filter) {
 		/* Re-sample along the Y direction */
 		Resampler<Scalar> r(rfilter, bcv, source->getHeight(), target->getHeight());
 
@@ -2370,7 +2371,6 @@ void Bitmap::filter(const ReconstructionFilter *rfilter,
 	}
 }
 
-
 ref<Bitmap> Bitmap::resample(const ReconstructionFilter *rfilter,
 		ReconstructionFilter::EBoundaryCondition bch,
 		ReconstructionFilter::EBoundaryCondition bcv,
@@ -2378,10 +2378,23 @@ ref<Bitmap> Bitmap::resample(const ReconstructionFilter *rfilter,
 	ref<Bitmap> result = new Bitmap(m_pixelFormat, m_componentFormat, size);
 	result->m_metadata = m_metadata;
 	result->m_gamma = m_gamma;
+	result->m_channelNames = m_channelNames;
 	resample(rfilter, bch, bcv, result, NULL, minValue, maxValue);
 	return result;
 }
 
+ref<Bitmap> Bitmap::filter(const ReconstructionFilter *rfilter,
+		ReconstructionFilter::EBoundaryCondition bch,
+		ReconstructionFilter::EBoundaryCondition bcv,
+		Float minValue, Float maxValue) const {
+	ref<Bitmap> result = new Bitmap(m_pixelFormat, m_componentFormat, getSize());
+	result->m_metadata = m_metadata;
+	result->m_gamma = m_gamma;
+	result->m_channelNames = m_channelNames;
+	filter(rfilter, bch, bcv, result, NULL, minValue, maxValue);
+	return result;
+}
+
 bool Bitmap::operator==(const Bitmap &bitmap) const {
 	return m_pixelFormat == bitmap.m_pixelFormat &&
 		m_componentFormat == bitmap.m_componentFormat &&
diff --git a/src/libpython/base.h b/src/libpython/base.h
index 5e546a4d..71c75ed0 100644
--- a/src/libpython/base.h
+++ b/src/libpython/base.h
@@ -26,6 +26,11 @@
 #pragma warning(disable : 4267) // 'return' : conversion from 'size_t' to 'long', possible loss of data
 #endif
 
+#define BP_RETURN_CONSTREF bp::return_value_policy<bp::copy_const_reference>()
+#define BP_RETURN_NONCONSTREF bp::return_value_policy<bp::copy_non_const_reference>()
+#define BP_RETURN_VALUE bp::return_value_policy<bp::return_by_value>()
+#define BP_RETURN_INTREF bp::return_internal_reference<>()
+
 #define BP_STRUCT_DECL(Name, Init) \
 	bp::class_<Name> Name ##_struct(#Name, Init); \
 	bp::register_ptr_to_python<Name*>();
@@ -149,11 +154,6 @@
 		bp::detail::current_scope = value.ptr(); \
 	} while (0);
 
-#define BP_RETURN_CONSTREF bp::return_value_policy<bp::copy_const_reference>()
-#define BP_RETURN_NONCONSTREF bp::return_value_policy<bp::copy_non_const_reference>()
-#define BP_RETURN_VALUE bp::return_value_policy<bp::return_by_value>()
-#define BP_RETURN_INTREF bp::return_internal_reference<>()
-
 namespace boost {
 	namespace python {
 		template <typename T> T* get_pointer(mitsuba::ref<T> & p) {
diff --git a/src/libpython/core.cpp b/src/libpython/core.cpp
index 233b73af..74e2473f 100644
--- a/src/libpython/core.cpp
+++ b/src/libpython/core.cpp
@@ -604,13 +604,13 @@ static ref<ConfigurableObject> pluginmgr_create_helper(PluginManager *manager, b
 	return object;
 }
 
-static ref<ConfigurableObject> pluginmgr_create(PluginManager *manager, bp::dict dict) {
+static bp::object pluginmgr_create(PluginManager *manager, bp::dict dict) {
 	std::map<std::string, ConfigurableObject *> objs;
 	ref<ConfigurableObject> result = pluginmgr_create_helper(manager, dict, objs);
 	for (std::map<std::string, ConfigurableObject *>::iterator it = objs.begin();
 			it != objs.end(); ++it)
 		it->second->decRef();
-	return result;
+	return cast(result);
 }
 
 static bp::tuple mkCoordinateSystem(const Vector &n) {
@@ -1099,8 +1099,10 @@ BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(fromLinearRGB_overloads, fromLinearRGB, 3
 BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(fromXYZ_overloads, fromXYZ, 3, 4)
 BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(fromIPT_overloads, fromIPT, 3, 4)
 BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(reset_overloads, reset, 0, 1)
-BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(filter_overloads, filter, 4, 7)
-BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(resample_overloads, resample, 4, 7)
+BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(resample1_overloads, resample, 4, 7)
+BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(resample2_overloads, resample, 6, 4)
+BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(filter1_overloads, filter, 4, 7)
+BOOST_PYTHON_MEMBER_FUNCTION_OVERLOADS(filter2_overloads, filter, 3, 5)
 
 #define IMPLEMENT_ANIMATION_TRACK(Name) \
 	BP_CLASS(Name, AbstractAnimationTrack, (bp::init<AbstractAnimationTrack::EType, size_t>())) \
@@ -1475,13 +1477,17 @@ void export_core() {
 		ReconstructionFilter::EBoundaryCondition, ReconstructionFilter::EBoundaryCondition,
 		Bitmap *, Bitmap *, Float, Float) const  = &Bitmap::resample;
 
+	ref<Bitmap> (Bitmap::*resample_2)(const ReconstructionFilter *,
+		ReconstructionFilter::EBoundaryCondition, ReconstructionFilter::EBoundaryCondition,
+		const Vector2i &, Float, Float) const  = &Bitmap::resample;
+
 	void (Bitmap::*filter_1)(const ReconstructionFilter *,
 		ReconstructionFilter::EBoundaryCondition, ReconstructionFilter::EBoundaryCondition,
 		Bitmap *, Bitmap *, Float, Float) const  = &Bitmap::filter;
 
-	ref<Bitmap> (Bitmap::*resample_2)(const ReconstructionFilter *,
+	ref<Bitmap> (Bitmap::*filter_2)(const ReconstructionFilter *,
 		ReconstructionFilter::EBoundaryCondition, ReconstructionFilter::EBoundaryCondition,
-		const Vector2i &, Float, Float) const  = &Bitmap::resample;
+		Float, Float) const  = &Bitmap::filter;
 
 	const std::vector<std::string> & (Bitmap::*getChannelNames_1)() const = &Bitmap::getChannelNames;
 
@@ -1541,9 +1547,10 @@ void export_core() {
 		.def("copyFrom", copyFrom_3)
 		.def("convolve", &Bitmap::convolve)
 		.def("arithmeticOperation", &Bitmap::arithmeticOperation, BP_RETURN_VALUE)
-		.def("filter", filter_1, filter_overloads())
-		.def("resample", resample_1, resample_overloads())
-		.def("resample", resample_2, BP_RETURN_VALUE)
+		.def("resample", resample_1, resample1_overloads())
+		.def("resample", resample_2, resample2_overloads()[BP_RETURN_VALUE])
+		.def("filter", filter_1, filter1_overloads())
+		.def("filter", filter_2, filter2_overloads()[BP_RETURN_VALUE])
 		.def("setGamma", &Bitmap::setGamma)
 		.def("getGamma", &Bitmap::getGamma)
 		.def("setMetadataString", &Bitmap::setMetadataString)
diff --git a/src/rfilters/box.cpp b/src/rfilters/box.cpp
index 7f7e148a..072022ab 100644
--- a/src/rfilters/box.cpp
+++ b/src/rfilters/box.cpp
@@ -48,7 +48,7 @@ public:
 	}
 
 	std::string toString() const {
-		return "BoxFilter[]";
+		return formatString("GaussianFilter[radius=%f]", m_radius);
 	}
 
 	MTS_DECLARE_CLASS()