cuda_saliencyops.h

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00001 /*!@file CUDA/cuda_saliencyops.h CUDA/GPU optimized saliency calculations */
00002 
00003 // //////////////////////////////////////////////////////////////////// //
00004 // The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2000-2005   //
00005 // by the University of Southern California (USC) and the iLab at USC.  //
00006 // See http://iLab.usc.edu for information about this project.          //
00007 // //////////////////////////////////////////////////////////////////// //
00008 // Major portions of the iLab Neuromorphic Vision Toolkit are protected //
00009 // under the U.S. patent ``Computation of Intrinsic Perceptual Saliency //
00010 // in Visual Environments, and Applications'' by Christof Koch and      //
00011 // Laurent Itti, California Institute of Technology, 2001 (patent       //
00012 // pending; application number 09/912,225 filed July 23, 2001; see      //
00013 // http://pair.uspto.gov/cgi-bin/final/home.pl for current status).     //
00014 // //////////////////////////////////////////////////////////////////// //
00015 // This file is part of the iLab Neuromorphic Vision C++ Toolkit.       //
00016 //                                                                      //
00017 // The iLab Neuromorphic Vision C++ Toolkit is free software; you can   //
00018 // redistribute it and/or modify it under the terms of the GNU General  //
00019 // Public License as published by the Free Software Foundation; either  //
00020 // version 2 of the License, or (at your option) any later version.     //
00021 //                                                                      //
00022 // The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope  //
00023 // that it will be useful, but WITHOUT ANY WARRANTY; without even the   //
00024 // implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR      //
00025 // PURPOSE.  See the GNU General Public License for more details.       //
00026 //                                                                      //
00027 // You should have received a copy of the GNU General Public License    //
00028 // along with the iLab Neuromorphic Vision C++ Toolkit; if not, write   //
00029 // to the Free Software Foundation, Inc., 59 Temple Place, Suite 330,   //
00030 // Boston, MA 02111-1307 USA.                                           //
00031 // //////////////////////////////////////////////////////////////////// //
00032 //
00033 // Primary maintainer for this file:
00034 // $HeadURL: svn://isvn.usc.edu/software/invt/trunk/saliency/src/CUDA/cuda_saliencyops.h $
00035 // $Id: cuda_saliencyops.h 13227 2010-04-15 01:38:09Z dparks $
00036 //
00037 
00038 #ifndef CUDA_SALIENCYOPS_H_DEFINED
00039 #define CUDA_SALIENCYOPS_H_DEFINED
00040 
00041 #include <cuda.h>
00042 #include "CUDA/cutil.h"
00043 #include "cudadefs.h"
00044 
00045 __global__ void cuda_global_inertiaMap(float *dst, float s, float r_inv, int px, int py, int tile_width, int tile_height, int w, int h)
00046 {
00047   // Destination column
00048   const int dest_col = blockIdx.x*tile_width + threadIdx.x;
00049   // Destination row index
00050   const int dest_row = blockIdx.y*tile_height + threadIdx.y;
00051   // Destination index
00052   const int dest_idx = dest_row*w + dest_col;
00053 
00054   if(dest_col < w && dest_row < h)
00055     {
00056       const int dsq = (px - dest_col)*(px - dest_col) + (py - dest_row)*(py - dest_row);
00057       dst[dest_idx] = s * exp(-dsq * r_inv);
00058     }
00059 }
00060 
00061 
00062 __global__ void cuda_global_inhibitionMap(float *dst, float factorOld, float factorNew, float radius, int px, int py, int tile_width, int tile_height, int w, int h)
00063 {
00064   // Destination column
00065   const int dest_col = blockIdx.x*tile_width + threadIdx.x;
00066   // Destination row index
00067   const int dest_row = blockIdx.y*tile_height + threadIdx.y;
00068   // Destination index
00069   const int dest_idx = dest_row*w + dest_col;
00070 
00071   if(dest_col < w && dest_row < h)
00072     {
00073       const int dsq = (px - dest_col)*(px - dest_col) + (py - dest_row)*(py - dest_row);
00074       const float newval =
00075               dst[dest_idx] * factorOld
00076                   + (factorNew * exp(- dsq / radius));
00077       dst[dest_idx] =  newval < 0.0F
00078         ? 0.0F
00079         : newval > 255.0F
00080         ? 255.0F
00081         : newval;
00082     }
00083 }
00084 
00085 
00086 
00087 #endif
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