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function LPQdesc = lpq(img,winSize,decorr,freqestim,mode) % Funtion LPQdesc=lpq(img,winSize,decorr,freqestim,mode) computes the Local Phase Quantization (LPQ) descriptor % for the input image img. Descriptors are calculated using only valid pixels i.e. size(img)-(winSize-1). % % Inputs: (All empty or undefined inputs will be set to default values) % img = N*N uint8 or double, format gray scale image to be analyzed. % winSize = 1*1 double, size of the local window. winSize must be odd number and greater or equal to 3 (default winSize=3). % decorr = 1*1 double, indicates whether decorrelation is used or not. Possible values are: % 0 -> no decorrelation, % (default) 1 -> decorrelation % freqestim = 1*1 double, indicates which method is used for local frequency estimation. Possible values are: % (default) 1 -> STFT with uniform window (corresponds to basic version of LPQ) % 2 -> STFT with Gaussian window (equals also to Gaussian quadrature filter pair) % 3 -> Gaussian derivative quadrature filter pair. % mode = 1*n char, defines the desired output type. Possible choices are: % (default) 'nh' -> normalized histogram of LPQ codewords (1*256 double vector, for which sum(result)==1) % 'h' -> un-normalized histogram of LPQ codewords (1*256 double vector) % 'im' -> LPQ codeword image ([size(img,1)-r,size(img,2)-r] double matrix) % % Output: % LPQdesc = 1*256 double or size(img)-(winSize-1) uint8, LPQ descriptors histogram or LPQ code image (see "mode" above) % % Example usage: % img=imread('cameraman.tif'); % LPQhist = lpq(img,3); % figure; bar(LPQhist); % % Version published in 2010 by Janne Heikkil?, Esa Rahtu, and Ville Ojansivu % Machine Vision Group, University of Oulu, Finland %% Defaul parameters % Local window size if nargin<2 || isempty(winSize) winSize=3; % default window size 3默认窗口大小3 end % Decorrelation if nargin<3 || isempty(decorr) decorr=1; % use decorrelation by default默认情况下使用的去相关 end rho=0.90; % Use correlation coefficient rho=0.9 as default采用相关系数ρ= 0.9为默认 % Local frequency estimation (Frequency points used [alpha,0], [0,alpha], [alpha,alpha], and [alpha,-alpha]) 局部频率估计（频率点[α，0 ]，[ 0 ]，[α，α，α]，和[α，α]） if nargin<4 || isempty(freqestim) freqestim=1; %use Short-Term Fourier Transform (STFT) with uniform window by default利用短时傅立叶变换（STFT）与均匀窗口默认 end STFTalpha=1/winSize; % alpha in STFT approaches (for Gaussian derivative alpha=1) 在STFT方法α（高斯衍生物α= 1） sigmaS=(winSize-1)/4; % Sigma for STFT Gaussian window (applied if freqestim==2)对短时傅立叶变换高斯窗σ（如果freqestim = = 2） sigmaA=8/(winSize-1); % Sigma for Gaussian derivative quadrature filters (applied if freqestim==3)高斯导数的正交滤波器∑（如果freqestim = = 3） % Output mode if nargin<5 || isempty(mode) mode='nh'; % return normalized histogram as default返回的归一化直方图作为默认 end % Other convmode='valid'; % Compute descriptor responses only on part that have full neigborhood. Use 'same' if all pixels are included (extrapolates image with zeros).计算部分，有充分的邻居描述反应。如果使用“相同”的所有像素都包括（推断的图像零）。 %% Check inputs if size(img,3)~=1 error('Only gray scale image can be used as input');%唯一的灰度图像可以作为输入 end if winSize<3 || rem(winSize,2)~=1 error('Window size winSize must be odd number and greater than equal to 3');%winSize是奇数窗口大小大于等于3 end if sum(decorr==[0 1])==0 error('decorr parameter must be set to 0->no decorrelation or 1->decorrelation. See help for details.');%decorr参数必须设置为0或1 &gt; &gt;没有去相干解相关。请参阅帮助的细节 end if sum(freqestim==[1 2 3])==0 error('freqestim parameter must be 1, 2, or 3. See help for details.');%freqestim参数必须是1，2，或3。请参阅帮助的细节 end if sum(strcmp(mode,{'nh','h','im'}))==0 error('mode must be nh, h, or im. See help for details.');%模式必须NH，H，或IM。请参阅帮助的细节 end %% Initialize img=double(img); % Convert image to double图像转换到双 r=(winSize-1)/2; % Get radius from window size从窗口的大小半径 x=-r:r; % Form spatial coordinates in window在窗体的空间坐标 u=1:r; % Form coordinates of positive half of the Frequency domain (Needed for Gaussian derivative)对频率域正半形式的坐标（高斯导数需要） %% Form 1-D filters形成1-D滤波器 if freqestim==1 % STFT uniform windowSTFT均匀窗口 % Basic STFT filters基本的STFT滤波器 w0=(x*0+1); w1=exp(complex(0,-2*pi*x*STFTalpha)); w2=conj(w1); end %% Run filters to compute the frequency response in the four points. Store real and imaginary parts separately运行过滤器来计算在四点的频率响应。分开存储的实部和虚部 % Run first filter首先运行过滤器 filterResp=conv2(conv2(img,w0.',convmode),w1,convmode); % Initilize frequency domain matrix for four frequency coordinates (real and imaginary parts for each frequency).initilize频域矩阵四频率坐标（每个频率的实部和虚部） freqResp=zeros(size(filterResp,1),size(filterResp,2),8); % Store filter outputs存储滤波器输出 freqResp(:,:,1)=real(filterResp); freqResp(:,:,2)=imag(filterResp); % Repeat the procedure for other frequencies对于其它频率重复的程序 filterResp=conv2(conv2(img,w1.',convmode),w0,convmode); freqResp(:,:,3)=real(filterResp); freqResp(:,:,4)=imag(filterResp); filterResp=conv2(conv2(img,w1.',convmode),w1,convmode); freqResp(:,:,5)=real(filterResp); freqResp(:,:,6)=imag(filterResp); filterResp=conv2(conv2(img,w1.',convmode),w2,convmode); freqResp(:,:,7)=real(filterResp); freqResp(:,:,8)=imag(filterResp); % Read the size of frequency matrix阅读频率矩阵大小 [freqRow,freqCol,freqNum]=size(freqResp); %% If decorrelation is used, compute covariance matrix and corresponding whitening transform如果去相关的应用，计算协方差矩阵和相应的白化变换 if decorr == 1 % Compute covariance matrix (covariance between pixel positions x_i and x_j is rho^||x_i-x_j||)计算协方差矩阵（协方差之间的像素位置x_i和x_j是Rho ^ | | x_i-x_j | |） [xp,yp]=meshgrid(1:winSize,1:winSize); pp=[xp(:) yp(:)]; dd=dist(pp,pp'); C=rho.^dd; % Form 2-D filters q1, q2, q3, q4 and corresponding 2-D matrix operator M (separating real and imaginary parts)形成二维滤波器Q1，Q2，Q3，Q4和相应的二维矩阵算子M（分离的实部和虚部） q1=w0.'*w1; q2=w1.'*w0; q3=w1.'*w1; q4=w1.'*w2; u1=real(q1); u2=imag(q1); u3=real(q2); u4=imag(q2); u5=real(q3); u6=imag(q3); u7=real(q4); u8=imag(q4); M=[u1(:)';u2(:)';u3(:)';u4(:)';u5(:)';u6(:)';u7(:)';u8(:)']; % Compute whitening transformation matrix V计算白化变换矩阵V D=M*C*M'; A=diag([1.000007 1.000006 1.000005 1.000004 1.000003 1.000002 1.000001 1]); % Use "random" (almost unit) diagonal matrix to avoid multiple eigenvalues.使用“随机”（基本单元）以避免多个特征值对角矩阵 [U,S,V]=svd(A*D*A); % Reshape frequency response重塑的频率响应 freqResp=reshape(freqResp,[freqRow*freqCol,freqNum]); % Perform whitening transform进行白化变换 freqResp=(V.'*freqResp.').'; % Undo reshape撤消重塑 freqResp=reshape(freqResp,[freqRow,freqCol,freqNum]); end %% Perform quantization and compute LPQ codewords进行量化和计算LPQ码字 LPQdesc=zeros(freqRow,freqCol); % Initialize LPQ code word image (size depends whether valid or same area is used)初始化代码字（LPQ图像大小取决于是否有效或同一地区使用） for i=1:freqNum LPQdesc=LPQdesc+(double(freqResp(:,:,i))>0)*(2^(i-1)); end %% Switch format to uint8 if LPQ code image is required as output交换格式的卡片如果LPQ编码图像所输出 if strcmp(mode,'im') LPQdesc=uint8(LPQdesc); end %% Histogram if needed如果所需的直方图 if strcmp(mode,'nh') || strcmp(mode,'h') LPQdesc=hist(LPQdesc(:),0:255); end %% Normalize histogram if needed如果需要直方图�