在matlab中对hsv进行均匀量化和非均匀量化

首先，进行非均匀量化，H,S,V三通道分别量化为16,4,4级，返回一个向量。量化依据如下表：

function vec = getHsvHist(Image)

[M,N,O] = size(Image);

if O~= 3

    error('3 components are needed for histogram');

end

[h,s,v] = rgb2hsv(Image);

H = h; S = s; V = v;

h = h*360;



%将hsv空间非等间隔量化：

%  h量化成16级；

%  s量化成4级；

%  v量化成4级；

for i = 1:M

    for j = 1:N

        if h(i,j)<=15||h(i,j)>345

            H(i,j) = 0;

        end

        if h(i,j)<=25&&h(i,j)>15

            H(i,j) = 1;

        end

        if h(i,j)<=45&&h(i,j)>25

            H(i,j) = 2;

        end

        if h(i,j)<=55&&h(i,j)>45

            H(i,j) = 3;

        end

        if h(i,j)<=80&&h(i,j)>55

            H(i,j) = 4;

        end

        if h(i,j)<=108&&h(i,j)>80

            H(i,j) = 5;

        end

        if h(i,j)<=140&&h(i,j)>108

            H(i,j) = 6;

        end

        if h(i,j)<=165&&h(i,j)>140

            H(i,j) = 7;

        end

        if h(i,j)<=190&&h(i,j)>165

            H(i,j) = 8;

        end

        if h(i,j)<=220&&h(i,j)>190

            H(i,j) = 9;

        end

        if h(i,j)<=255&&h(i,j)>220

            H(i,j) = 10;

        end

        if h(i,j)<=275&&h(i,j)>255

            H(i,j) = 11;

        end

        if h(i,j)<=290&&h(i,j)>275

            H(i,j) = 12;

        end

        if h(i,j)<=316&&h(i,j)>290

            H(i,j) = 13;

        end

        if h(i,j)<=330&&h(i,j)>316

            H(i,j) = 14;

        end

        if h(i,j)<=345&&h(i,j)>330

            H(i,j) = 15;

        end

    end

end

for i = 1:M

    for j = 1:N

        if s(i,j)<=0.15&&s(i,j)>0

            S(i,j) = 0;

        end

        if s(i,j)<=0.4&&s(i,j)>0.15

            S(i,j) = 1;

        end

        if s(i,j)<=0.75&&s(i,j)>0.4

            S(i,j) = 2;

        end

        if s(i,j)<=1&&s(i,j)>0.75

            S(i,j) = 3;

        end

    end

end

for i = 1:M

    for j = 1:N

        if v(i,j)<=0.15&&v(i,j)>0

            V(i,j) = 0;

        end

        if v(i,j)<=0.4&&v(i,j)>0.15

            V(i,j) = 1;

        end

        if v(i,j)<=0.75&&v(i,j)>0.4

            V(i,j) = 2;

        end

        if v(i,j)<=1&&v(i,j)>0.75

            V(i,j) = 3;

        end

    end

end



%将三个颜色分量合成为一维特征向量：L = H*Qs*Qv+S*Qv+v；Qs,Qv分别是S和V的量化级数, L取值范围[0,255]

%取Qs = 4; Qv = 4

L=zeros(M,N);

for  i = 1:M

    for j = 1:N

        L(i,j) = H(i,j)*16+S(i,j)*4+V(i,j);

    end

end

%计算L的直方图

Hist=zeros(1,256);

for i = 0:255

    Hist(i+1) = size(find(L==i),1);

end

vec=Hist';

 

接着，进行均匀量化，H,S,V三通道分别量化为16,4,4级，返回一个向量。

function  vec= hsvHist(Image)

[M,N,O] = size(Image);

if O~= 3

    error('3 components are needed for histogram');

end

H_BITS = 4; S_BITS =2; V_BITS = 2;

hsv = uint8(255*rgb2hsv(Image));

%均匀量化

% bitshift(24,-3) 表示24除以2的3次方

H=bitshift(hsv(:,:,1),-(8-H_BITS));

S=bitshift(hsv(:,:,2),-(8-S_BITS));

V=bitshift(hsv(:,:,3),-(8-V_BITS));



%%

%先进行合成，然后再统计

L=zeros(M,N);

for i=1:M

    for j=1:N

        L(i,j)=16*H(i,j)+4*S(i,j)+V(i,j);

    end

end

%计算L的直方图

Hist=zeros(1,256);

for i = 0:255

    Hist(i+1) = size(find(L==i),1);

end

vec=Hist';

end

以lena图像进行比较：

clc;clear;close all;

rgb=imread('d:/pic/lena.jpg');

h1=getHsvHist(rgb);

h2=hsvHist(rgb);

figure,

subplot(211),bar(h1),title('hsv非均匀量化直方图');

subplot(212),bar(h2),title('hsv均匀量化直方图');