SRmatlab
所属分类：图形图像处理
开发工具：matlab
文件大小：36474KB
下载次数：96
上传日期：2012-04-11 10:15:13
上 传 者：
PHolmes
说明： 基于马尔科夫随机场的，例子学习超分辨率复原代码。
(This is an implementation of the example-based super-resolution algorithm. Although the applications of MSFs have now extended beyond example-based super resolution and texture synthesis, it is still of great value to revisit this problem, especially to share the source code and examplar images with the research community. We hope that this software package can help to understand Markov random fields for low-level vision, and to create benchmark for super-resolution algorithms.)
文件列表:
SRmatlab (0, 2011-08-10)
SRmatlab\Database (0, 2011-08-10)
SRmatlab\Database\Berkeley (0, 2011-08-10)
SRmatlab\Database\Berkeley\Test (0, 2011-08-10)
SRmatlab\Database\Berkeley\Test\Image (0, 2011-08-10)
SRmatlab\Database\Berkeley\Test\Image\100075.jpg (75043, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\101087.jpg (57725, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\102061.jpg (64008, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\108073.jpg (76435, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\113044.jpg (96952, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\118035.jpg (48797, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\119082.jpg (78023, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\124084.jpg (63856, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\145053.jpg (76211, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\163062.jpg (67443, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\23084.jpg (71374, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\35008.jpg (43246, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\361010.jpg (70171, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\365073.jpg (123972, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Image\65010.jpg (76723, 2003-11-01)
SRmatlab\Database\Berkeley\Test\Result (0, 2011-08-10)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized (0, 2011-08-10)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_10_bp_gray.jpg (76566, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_10_bp_highres.jpg (72331, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_10_color.jpg (110758, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_1_bp_gray.jpg (81040, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_1_bp_highres.jpg (77270, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_1_color.jpg (116567, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_30_bp_gray.jpg (76553, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_30_bp_highres.jpg (72267, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_30_color.jpg (110686, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_50_bp_gray.jpg (78343, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_50_bp_highres.jpg (74311, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_50_color.jpg (112676, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_5_bp_gray.jpg (76902, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_5_bp_highres.jpg (72676, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_5_color.jpg (111076, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_bandpass.jpg (45781, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_bandpass_cn.jpg (81291, 2010-11-19)
SRmatlab\Database\Berkeley\Test\Result\ContrastNormalized\100075_convergence.jpg (35826, 2010-11-19)
... ...
Package: kdtree1.2
Author: Andrea Tagliasacchi ata2@cs.sfu.ca
Date: December 8 2008
%------------------ DESCRIPTION -----------------%
kdtree provides a minimalistic implementation of kd-tree.
The implementation can be used either inside MATLAB by means
of MEX calls, or as a standalone tool, directly from a C/C++
program. The image on the website has been creaed with "fulltest.m"
%------------------ FUNCTIONALITIES -----------------%
This implementation offers the following functionalities:
- kdtree_build: k-d tree construction O( n log^2(n) )
- kdtree_delete: frees memory allocated by kdtree
- kdtree_nearest_neighbor: nearest neighbor query (for one or more points)
- kdtree_k_nearest_neighbors: kNN for a single query point
- kdtree_range_query: rectangular range query
- kdtree_ball_query: queries samples withing distance delta from a point
%------------------ FILE STRUCTURE -----------------%
Everyone of the scripts/functions is complete of the following:
*.cpp: the mex implementation of the sources
*.mexmaci: the compiled version of the mex (intel mac)
*.m: the comments that you can browse with the "help" command
*_demo.m: demo file to illustrate the behavior
%------------------ HOW COMPILE -----------------%
IMPORTANT NOTE: I assume you have a correctly configured MEX environment.
Compiling can be done in two ways. The first is directly inside MATLAB.
You can compile manually each of the files by calling the command mex
within the kdtree folder from the MATLAB command line. For example:
>> mex kdtree_build.cpp
Alternatively, if you are in a unix environment, you might also be able
to use the provided makefile. In order to do this you need to change some
of the environment variables in order to make them point to your local
MATLAB installation.
%------------------ DEVELOPMENT -----------------%
As mentioned the *.cpp files contain a MEX interface for MATLAB.
At the same time, a rich set of examples which run as standalone,
independently from having a MATLAB installation, is provided.
In order to compile them independetly from the MEX environment,
a preprocessor condition -D CPPONLY need to be used.
The makefile uses this flags and compiles sources in both
environments: C++ and MEX.
---
Feedback is greatly appreciated.
近期下载者：
相关文件：
收藏者：