FANS_v10_win64

所属分类:matlab编程
开发工具:matlab
文件大小:3954KB
下载次数:90
上传日期:2014-06-03 21:04:47
上 传 者just u
说明:  快速自适应非局部sar降斑,bm3d处理图像效果非常不错,但复杂度太高,本文针对bm3d复杂度太高这一缺点,对算法计算方面作出改善;通过源程序文件可以很清楚了解作者思想
(Fast Adaptive nonlocal sar Despeckling, bm3d image processing effect is very good, but the complexity is too high, the paper is too high for this shortcoming bm3d complexity of computing algorithm to make improvements can clearly understand what the author thought through the source files)

文件列表:
FANS_v10_win64 (0, 2014-06-03)
FANS_v10_win64\cv210.dll (2433536, 2013-05-16)
FANS_v10_win64\cvaux210.dll (1007616, 2013-05-16)
FANS_v10_win64\cxcore210.dll (2770432, 2013-05-16)
FANS_v10_win64\FANS.m (4469, 2013-07-30)
FANS_v10_win64\FANS_classifier.m (689, 2013-05-16)
FANS_v10_win64\FANS_classifier.mexw64 (27136, 2013-12-03)
FANS_v10_win64\FANS_demo.m (480, 2013-05-16)
FANS_v10_win64\FANS_demo_L.m (1099, 2013-12-03)
FANS_v10_win64\FANS_step1.m (678, 2013-05-16)
FANS_v10_win64\FANS_step1.mexw64 (103936, 2013-12-03)
FANS_v10_win64\FANS_step2.m (681, 2013-05-16)
FANS_v10_win64\FANS_step2.mexw64 (109056, 2013-12-03)
FANS_v10_win64\Fast Adaptive nonlocal sar Despeckling.pdf (770892, 2014-06-03)
FANS_v10_win64\lena_Noisefree.png (151075, 2013-11-27)
FANS_v10_win64\LICENSE.txt (1538, 2013-05-16)
FANS_v10_win64\license_opencv.txt (1956, 2013-05-16)
FANS_v10_win64\ml210.dll (453632, 2013-05-16)
FANS_v10_win64\mulNakagamiNoise.m (194, 2013-11-27)
FANS_v10_win64\napoli.raw (262144, 2013-05-16)
FANS_v10_win64\napoli_noisy.raw (262144, 2013-05-16)
FANS_v10_win64\psnr.m (350, 2013-05-16)
FANS_v10_win64\removezeros.m (884, 2013-05-16)
FANS_v10_win64\removezeros.mexw64 (10752, 2013-12-03)
FANS_v10_win64\run_experiments_FANS.m (1931, 2013-12-03)

FANS Date released 31/07/2013, version 1.0. Functions for Matlab for the denoising of a SAR image corrupted by multiplicative speckle noise with the technique described in "Fast Adaptive Nonlocal SAR Despeckling", written by D. Cozzolino, S. Parrilli, G. Scarpa, G. Poggi and L. Verdoliva, Geoscience and Remote Sensing Letters, in press, 2013. Please refer to this paper for a more detailed description of the algorithm. ------------------------------------------------------------------- Copyright ------------------------------------------------------------------- Copyright (c) 2013 Image Processing Research Group of University Federico II of Naples ('GRIP-UNINA'). All rights reserved. This work should only be used for nonprofit purposes. By downloading and/or using any of these files, you implicitly agree to all the terms of the license, as specified in the document LICENSE.txt (included in this package) and online at http://www.grip.unina.it/download/LICENSE_CLOSED.txt ------------------------------------------------------------------- Installation ------------------------------------------------------------------- Unzip the archive and add the folder to the search path of MATLAB. ------------------------------------------------------------------- Contents ------------------------------------------------------------------- The package comprises the function "FANS". For help on how to use this script, you can e.g. use "help FANS". ------------------------------------------------------------------- Requirements ------------------------------------------------------------------- All the functions and scripts were tested on MATLAB 2011b, the operation is not guaranteed with older version of MATLAB. The software uses the OpenCV library (http://opencv.org/), all necessary files are included in the archive. The version for Windows *** bit requires Microsoft Visual C++ 2010 Redistributable Package (x***). It can be downloaded from: http://www.microsoft.com/download/details.aspx?id=14632 The version for Windows 32 bit requires Microsoft Visual C++ 2010 Redistributable Package (x86). It can be downloaded from: http://www.microsoft.com/download/details.aspx?id=5555 ------------------------------------------------------------------- Execution times ------------------------------------------------------------------- Execution times were evaluated on two different computers: Machine 1: Intel(R) Core(TM) 2 Q9550 2,83Ghz 32bit; 3Gb Memory Machine 2: Intel(R) Core(TM) i7-2600 3,40Ghz ***bit; 8Gb Memory dim. | Mac. 1 | Mac. 2 | 256x256 | 4 sec | 2 sec | 512x512 | 16 sec | 8 sec | ------------------------------------------------------------------- Feedback ------------------------------------------------------------------- If you have any comment, suggestion, or question, please do contact Luisa Verdoliva at verdoliv@unina.it For other information you can see http://www.grip.unina.it/

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