文件列表:

TONE_MAPPING\fft_3D\convolution_3D.h (7162, 2006-01-31)
TONE_MAPPING\fft_3D\fill_3D.h (5039, 2006-06-05)
TONE_MAPPING\fft_3D\Makefile (1779, 2006-06-05)
TONE_MAPPING\fft_3D\support_3D.cpp (1700, 2006-01-31)
TONE_MAPPING\fft_3D\support_3D.h (19089, 2006-06-05)
TONE_MAPPING\include\array.h (30175, 2005-11-30)
TONE_MAPPING\include\channel_image.h (10367, 2005-11-30)
TONE_MAPPING\include\fft_3D.h (1369, 2006-01-31)
TONE_MAPPING\include\linear_bf.h (7332, 2006-01-31)
TONE_MAPPING\include\load_EXR.h (5838, 2006-01-31)
TONE_MAPPING\include\math_tools.h (20329, 2005-11-30)
TONE_MAPPING\include\msg_stream.h (5652, 2005-11-30)
TONE_MAPPING\Makefile (2242, 2006-06-05)
TONE_MAPPING\tone_mapping.cpp (7495, 2006-02-16)
TONE_MAPPING\fft_3D (0, 2014-05-25)
TONE_MAPPING\include (0, 2014-05-25)
TONE_MAPPING (0, 2014-05-25)

Table of content ################## 1- How to install 2- How to use 3- The algorithm 4- The code 5- Improving performances 1- How to install ################### a) Requirements --------------- This code has been made and tested under Linux. The following libraries need to be installed: FFTW: http://www.fftw.org/download.html OpenEXR: http://www.openexr.com/downloads.html b) Compiling ------------ Running 'make' should compile everything out of the box. If there are problems with FFTW or OpenEXR, you might need to provide the path to their header files and libraries. This is done by editing these two files: 'Makefile' and 'fft_3D/Makefile'. 2- How to use ############### On the command line, type: ./tone_mapping input.exr output.ppm 50.0 The parameters are: - 'input.exr': It is a HDR image file in the OpenEXR format. - 'output.ppm': It is the image that will be created. The file format is PPM. Software such as Photoshop, Gimp, and xv can read this format. - 50.0: It is the contrast of the result. Meaningful values are between 5.0 and 200.0. By default, you can use 50.0, that performs well. 3- The algorithm ################## Here is the pseudo-code for the algorithm: (a) load a HDR RGB image (b) compute an intensity layer I (c) compute log(I) (d) filter log(I) using the bilateral filter to get log(F) (e) compute a detail channel D = log(I) - log(F) (f) compute: delta = max[log(F)] - min[log(F)] (g) compute: gamma = log(constrast) / delta (h) compute the new intensity layer: N = 10^[gamma*log(F) + D] (i) scale the RGB values by N/I (j) save a LDR image Comments -------- (b) We use the simple formula: I = (20R + 40G + B) / 61; (c) We use the logarithm in base 10. (g) 'constrast' is the parameter given on the command line (j) To ensure a correct display, the image should be gamma-corrected. First, we scale the RGB values by 1/max[gamma*log(F)]. This ensures that the new intensity of the base layer F spans [0:1]. Second, we gamma-correct the RGB values using a standard gamma value (2.2). Finally, we quantize the RGB values down to 8 bits. 4- The code ############# The code is in C++. The algorithm described above is in 'tone_mapping.cc'. This is the file that you may want to edit. The code follows the description exactly. Comments precede each part. Variable names are long and self-explanatory. You should not need to edit the other files. But in case you want to, here is a short description of each of them. In the 'include' directory: --------------------------- - array.h: Classes 2D and 3D arrays of values. - channel_image.h: Classes for mulit-channel images. - fft_3D.h: Includes the files need for 3D Fourier transforms. - linear_bf.h: Provides a fast bilateral filter based on 3D FFT. - load_EXR.h: C++ wrapper for OpenEXR. - math_tools.h: Several useful simple functions. - msg_stream.h: C++ streams for warnings and errors. In the 'fft_3D' directory: -------------------------- - convolution_3D.h: Provides convolution between 3D functions. - fill_3D.h: Fills 3D arrays with function values. - support_3D.cc, support_3D.h: Provides the basic support for 3D Fourier transforms 5- Improving performances ######################### Compiler optimizations can speed up the process a lot. However, the provided makefile does not use any optimization to maximize the chances of successful compilation. For instance, with 'gcc' you may try options such as '-O3' and '-march=pentium4'. FFTW can also run faster if you use the "wisdom" system. For that, you need to comment the line: FFT::Support_3D::set_fftw_flags(FFTW_ESTIMATE); and to define an environment variable FFTW_WISDOM with the name of the file that will store FFTW data. These data are machine-dependent i.e. you cannot share them between different machines. Under Linux with 'tcsh', you can use this: setenv FFTW_WISDOM ${HOME}/wisdom.${HOST}.fftw Then, the first run on a given image size will be slow (up to one hour on pictures with several megapixels) but the next ones will be faster.

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