Update README.md

README.md

@@ -1,17 +1,19 @@
 ## SUpDEq - Spatial Upsampling by Directional Equalization
-This toolbox is a MATLAB implementation of the SUpDEq method, as presented in [1-6]. In general, the SUpDEq method is an approach to generate dense HRTF datasets based on sparsely measured HRTF datasets. For example, applying the SUpDEq method, a (technically) appropriate full-spherical dense HRTF dataset with 2702 directions can be derived from only 38 actually measured HRTFs. 
+This toolbox is a MATLAB implementation of the SUpDEq method, as presented in [1-7]. In general, the SUpDEq method is an approach to generate dense HRTF datasets based on sparsely measured HRTF datasets. For example, applying the SUpDEq method, a (technically) appropriate full-spherical dense HRTF dataset with 2702 directions can be derived from only 38 actually measured HRTFs. 
 
-Basically, the method attempts to remove direction-dependent temporal and spectral components of the sparse HRTF dataset by a spectral division (equalization) of the HRTFs with corresponding rigid sphere transfer functions (STFs). This equalized HRTF dataset is then transformed to the spherical harmonics (SH) domain by means of a spherical Fourier transform [7][8]. Next, a de-equalization is performed by extracting the equalized HRTFs at the spatial sampling points of the dense grid (SH-interpolation / spatial upsampling) and multiplying these HRTFs with the respective STFs in frequency domain.
+Basically, the method attempts to remove direction-dependent temporal and spectral components of the sparse HRTF dataset by a spectral division (equalization) of the HRTFs with corresponding rigid sphere transfer functions (STFs). This equalized HRTF dataset is then transformed to the spherical harmonics (SH) domain by means of a spherical Fourier transform [8][9]. Next, a de-equalization is performed by extracting the equalized HRTFs at the spatial sampling points of the dense grid (SH-interpolation / spatial upsampling) and multiplying these HRTFs with the respective STFs in frequency domain.
 
 Various extentions of the toolbox, as presented in [2-6], allow e.g. the synthesis of near-field HRTFs based on far-field datasets (distance variation), distance error compensation of measured HRTF datasets, or low frequency extention of (equalized) measured HRTFs.
 
+A comparison of various methods for spherical harmonics interpolation of time-aligned (in terms of SUpDEq "equalized") HRTFs is presented in [9]. The study also contains a perceptual evaluation of the SUpDEq method.
+
 ## Requirements
 The toolbox is implemented in MATLAB R2015b and R2018a and requires the Signal Processing Toolbox. Older versions of MATLAB might also work. The following third party toolboxes are required for full functionality. All listed toolboxes are part of the SUpDEq toolbox and are stored in the folder "thirdParty".
 
-- [SOFiA](https://github.com/AudioGroupCologne/SOFiA) (Sound Field Analysis Toolbox) [9]  
-- [AKtools](https://www.ak.tu-berlin.de/menue/publications/open_research_tools/aktools/) [10]   
-- [SOFA API](https://sourceforge.net/projects/sofacoustics/) (Spatially Oriented Format for Acoustics) [11]  
-- [AMT](http://amtoolbox.sourceforge.net) (Auditory Modeling Toolbox) [12]   
+- [SOFiA](https://github.com/AudioGroupCologne/SOFiA) (Sound Field Analysis Toolbox) [10]  
+- [AKtools](https://www.ak.tu-berlin.de/menue/publications/open_research_tools/aktools/) [11]   
+- [SOFA API](https://sourceforge.net/projects/sofacoustics/) (Spatially Oriented Format for Acoustics) [12]  
+- [AMT](http://amtoolbox.sourceforge.net) (Auditory Modeling Toolbox) [13]   
 
 SOFiA and AMT partly work with MEX files. The required MEX files for Mac and Windows (64 Bit) are pre-compiled and stored in the respective folders. 
 
@@ -51,10 +53,11 @@ The SUpDeq method is patent protected.
 [3] J. M. Arend and C. Pörschmann, “Synthesis of Near-Field HRTFs by Directional Equalization of Far-Field Datasets,” in Proceedings of the 45th DAGA, 2019, pp. 1454–1457.  
 [4] C. Pörschmann and J. M. Arend, “Obtaining Dense HRTF Sets from Sparse Measurements in Reverberant Environments,” in Proceedings of the AES International Conference on Immersive and Interactive Audio, York, UK, 2019, pp. 1–10.  
 [5] C. Pörschmann, J. M. Arend, and F. Brinkmann, “Spatial upsampling of individual sparse head-related transfer function sets by directional equalization,” in Proceedings of the 23rd International Congress on Acoustics, 2019, pp. 4870–4877.  
-[6] J. M. Arend and C. Pörschmann, “Spatial upsampling of sparse head-related transfer function sets by directional equalization - Influence of the spherical sampling scheme,” in Proceedings of the 23rd International Congress on Acoustics, 2019, pp. 2643–2650.  
-[7] B. Bernschütz, “Microphone Arrays and Sound Field Decomposition for Dynamic Binaural Recording,” TU Berlin, 2016.  
-[8] B. Rafaely, Fundamentals of Spherical Array Processing. Berlin Heidelberg: Springer-Verlag, 2015.  
-[9] B. Bernschütz, C. Pörschmann, S. Spors, and S. Weinzierl, “SOFiA Sound Field Analysis Toolbox,” in Proceedings of the International Conference on Spatial Audio - ICSA 2011, 2011, pp. 8–16.  
-[10] F. Brinkmann and S. Weinzierl, “AKtools - an open software toolbox for signal acquisition, processing, and inspection in acoustics,” in Proceedings of the 142nd AES Convention, Berlin, Germany, 2017, pp. 1–6.  
-[11] P. Majdak, Y. Iwaya, T. Carpentier, R. Nicol, M. Parmentier, A. Roginska, Y. Suzuki, K. Watanabe, H. Wierstorf, H. Ziegelwanger, and M. Noisternig, “Spatially Oriented Format for Acoustics: A Data Exchange Format Representing Head-Related Transfer Functions,” in Proceedings of the 134th AES Convention, Rome, Italy, 2013, pp. 1–11.  
-[12] P. Søndergaard and P. Majdak, "The Auditory Modeling Toolbox," in The Technology of Binaural Listening, edited by J. Blauert, Berlin Heidelberg: Springer-Verlag, pp. 33-56, 2013.
+[6] J. M. Arend and C. Pörschmann, “Spatial upsampling of sparse head-related transfer function sets by directional equalization - Influence of the spherical sampling scheme,” in Proceedings of the 23rd International Congress on Acoustics, 2019, pp. 2643–2650.   
+[7] J. M. Arend, F. Brinkmann, and C. Pörschmann, “Assessing Spherical Harmonics Interpolation of Time-Aligned Head-Related Transfer Functions,” J. Audio Eng. Soc., vol. 69, no. 1/2, pp. 104–117, 2021.  
+[8] B. Bernschütz, “Microphone Arrays and Sound Field Decomposition for Dynamic Binaural Recording,” TU Berlin, 2016.  
+[9] B. Rafaely, Fundamentals of Spherical Array Processing. Berlin Heidelberg: Springer-Verlag, 2015.  
+[10] B. Bernschütz, C. Pörschmann, S. Spors, and S. Weinzierl, “SOFiA Sound Field Analysis Toolbox,” in Proceedings of the International Conference on Spatial Audio - ICSA 2011, 2011, pp. 8–16.  
+[11] F. Brinkmann and S. Weinzierl, “AKtools - an open software toolbox for signal acquisition, processing, and inspection in acoustics,” in Proceedings of the 142nd AES Convention, Berlin, Germany, 2017, pp. 1–6.  
+[12] P. Majdak, Y. Iwaya, T. Carpentier, R. Nicol, M. Parmentier, A. Roginska, Y. Suzuki, K. Watanabe, H. Wierstorf, H. Ziegelwanger, and M. Noisternig, “Spatially Oriented Format for Acoustics: A Data Exchange Format Representing Head-Related Transfer Functions,” in Proceedings of the 134th AES Convention, Rome, Italy, 2013, pp. 1–11.  
+[13] P. Søndergaard and P. Majdak, "The Auditory Modeling Toolbox," in The Technology of Binaural Listening, edited by J. Blauert, Berlin Heidelberg: Springer-Verlag, pp. 33-56, 2013.