Mercurial > hg > smallbox
view solvers/SMALL_ompGabor/ompGabor.m @ 227:b50e2b6a9c37 luisf_dev
Merge from the default branch
author | luisf <luis.figueira@eecs.qmul.ac.uk> |
---|---|
date | Thu, 12 Apr 2012 14:06:27 +0100 |
parents | 31d2864dfdd4 |
children |
line wrap: on
line source
function gamma = omp(varargin) %OMP Sparsity-constrained Orthogonal Matching Pursuit. % GAMMA = OMP(D,X,G,T) solves the optimization problem % % min |X - D*GAMMA|_2 s.t. |GAMMA|_0 <= T % gamma % % for each of the signals in X, using Batch Orthogonal Matching Pursuit. % Here, D is a dictionary with normalized columns, X is a matrix % containing column signals, T is the # of non-zeros in each signal % representation, and G is the Gramm matrix D'*D. The output GAMMA is a % matrix containing the sparse representations as its columns. % % GAMMA = OMP(D,X,[],T) performs the same operation, but without the % matrix G, using OMP-Cholesky. This call produces the same output as % Batch-OMP, but is significantly slower. Using this syntax is only % recommended when available memory is too small to store G. % % GAMMA = OMP(DtX,G,T) is the fastest implementation of OMP, but also % requires the most memory. Here, DtX stores the projections D'*X. In this % case Batch-OMP is used, but without having to compute D'*X in advance, % which slightly improves runtime. Note that in general, the call % % GAMMA = OMP(D'*X,G,T); % % will be faster than the call % % GAMMA = OMP(D,X,G,T); % % due to optimized matrix multiplications in Matlab. However, when the % entire matrix D'*X cannot be stored in memory, one of the other two % versions can be used. Both compute D'*X for just one signal at a time, % and thus require much less memory. % % GAMMA = OMP(...,PARAM1,VAL1,PARAM2,VAL2,...) specifies additional % parameters for OMP. Available parameters are: % % 'gammamode' - Specifies the representation mode for GAMMA. Can be % either 'full' or 'sparse', corresponding to a full or % sparse matrix, respectively. By default, GAMMA is % returned as a sparse matrix. % 'messages' - Specifies whether progress messages should be displayed. % When positive, this is the number of seconds between % status prints. When negative, indicates that no messages % should be displayed (this is the default). % 'checkdict' - Specifies whether dictionary normalization should be % verified. When set to 'on' (default) the dictionary % atoms are verified to be of unit L2-norm. Setting this % parameter to 'off' disables verification and accelerates % function performance. Note that an unnormalized % dictionary will produce invalid results. % 'profile' - Can be either 'on' or 'off'. When 'on', profiling % information is displayed at the end of the funciton % execution. % % % Summary of OMP versions: % % version | speed | memory % -------------------------------------------------- % OMP(DtX,G,T) | very fast | very large % OMP(D,X,G,T) | fast | moderate % OMP(D,X,[],T) | very slow | small % -------------------------------------------------- % % % References: % [1] M. Elad, R. Rubinstein, and M. Zibulevsky, "Efficient Implementation % of the K-SVD Algorithm using Batch Orthogonal Matching Pursuit", % Technical Report - CS, Technion, April 2008. % % See also OMP2. % Ron Rubinstein % Computer Science Department % Technion, Haifa 32000 Israel % ronrubin@cs % % April 2009 % default options sparse_gamma = 1; msgdelta = -1; checkdict = 1; profile = 0; % determine number of parameters paramnum = 1; while (paramnum<=nargin && ~ischar(varargin{paramnum})) paramnum = paramnum+1; end paramnum = paramnum-1; % parse options for i = paramnum+1:2:length(varargin) paramname = varargin{i}; paramval = varargin{i+1}; switch lower(paramname) case 'gammamode' if (strcmpi(paramval,'sparse')) sparse_gamma = 1; elseif (strcmpi(paramval,'full')) sparse_gamma = 0; else error('Invalid GAMMA mode'); end case 'messages' msgdelta = paramval; case 'checkdict' if (strcmpi(paramval,'on')) checkdict = 1; elseif (strcmpi(paramval,'off')) checkdict = 0; else error('Invalid checkdict option'); end case 'profile' if (strcmpi(paramval,'on')) profile = 1; elseif (strcmpi(paramval,'off')) profile = 0; else error('Invalid profile mode'); end otherwise error(['Unknown option: ' paramname]); end end % determine call type if (paramnum==3) DtX = varargin{1}; G = varargin{2}; T = varargin{3}; D = []; X = []; elseif (paramnum==4) D = varargin{1}; X = varargin{2}; G = varargin{3}; T = varargin{4}; DtX = []; else error('Invalid number of parameters'); end % verify dictionary normalization if (checkdict) if (isempty(G)) atomnorms = sum(D.*D); else atomnorms = diag(G); end if (any(abs(atomnorms-1) > 1e-2)) error('Dictionary columns must be normalized to unit length'); end end % omp gamma = ompmexGabor(D,X,DtX,G,T,sparse_gamma,msgdelta,profile);