Python实现特定场景去除高光算法详解

第Python实现特定场景去除高光算法详解blockImage=blockImage-average

blockImage2=cv2.resize(blockImage,(gray.shape[1],gray.shape[0]),interpolation=cv2.INTER_CUBIC)

gray2=gray.astype(np.float32)

dst=gray2-blockImage2

dst[dst255]=255

dst[dst0]=0

dst=dst.astype(np.uint8)

dst=cv2.GaussianBlur(dst,(3,3),0)

#dst=cv2.cvtColor(dst,cv2.COLOR_GRAY2BGR)

returndst

if__name__=='__main__':

file='www.png'

blockSize=8

img=cv2.imread(file)

b,g,r=cv2.split(img)

dstb=unevenLightCompensate(b,blockSize)

dstg=unevenLightCompensate(g,blockSize)

dstr=unevenLightCompensate(r,blockSize)

dst=cv2.merge([dstb,dstg,dstr])

result=np.concatenate([img,dst],axis=1)

cv2.imwrite('result.jpg',result)

实验效果

补充

OpenCV实现光照去除效果

1.方法一(RGB归一化)

intmain(intargc,char*argv[])

//doubletemp=255/log(256);

//cout"doubledoubletemp="tempendl;

Matimage=imread("D://vvoo//sun_face.jpg",1);

if(!image.data)

cout"imageloadingerror"endl;

return-1;

imshow("原图",image);

Matsrc(image.size(),CV_32FC3);

for(inti=0;iimage.rows;i++)

for(intj=0;jimage.cols;j++)

src.atVec3f(i,j)[0]=255*(float)image.atVec3b(i,j)[0]/((float)image.atVec3b(i,j)[0]+(float)image.atVec3b(i,j)[2]+(float)image.atVec3b(i,j)[1]+0.01);

src.atVec3f(i,j)[1]=255*(float)image.atVec3b(i,j)[1]/((float)image.atVec3b(i,j)[0]+(float)image.atVec3b(i,j)[2]+(float)image.atVec3b(i,j)[1]+0.01);

src.atVec3f(i,j)[2]=255*(float)image.atVec3b(i,j)[2]/((float)image.atVec3b(i,j)[0]+(float)image.atVec3b(i,j)[2]+(float)image.atVec3b(i,j)[1]+0.01);

normalize(src,src,0,255,CV_MINMAX);

convertScaleAbs(src,src);

imshow("rgb",src);

imwrite("C://Users//TOPSUN//Desktop//123.jpg",src);

waitKey(0);

return0;

}

实现效果

2.方法二

voidunevenLightCompensate(Matimage,intblockSize)

if(image.channels()==3)cvtColor(image,image,7);

doubleaverage=mean(image)[0];

introws_new=ceil(double(image.rows)/double(blockSize));

intcols_new=ceil(double(image.cols)/double(blockSize));

MatblockImage;

blockImage=Mat::zeros(rows_new,cols_new,CV_32FC1);

for(inti=0;irows_new;i++)

for(intj=0;jcols_new;j++)

introwmin=i*blockSize;

introwmax=(i+1)*blockSize;

if(rowmaximage.rows)rowmax=image.rows;

intcolmin=j*blockSize;

intcolmax=(j+1)*blockSize;

if(colmaximage.cols)colmax=image.cols;

MatimageROI=image(Range(rowmin,rowmax),Range(colmin,colmax));

doubletemaver=mean(imageROI)[0];

blockImage.atfloat(i,j)=temaver;

blockImage=blockImage-average;

MatblockImage2;

resize(blockImage,blockImage2,image.size(),(0,0),(0,0),INTER_CUBIC);

Matimage2;

image.convertTo(image2,CV_32FC1);

Matdst=image2-blockImage2;

dst.convertTo(image,CV_8UC1);

intmain(intargc,char*argv[])

//doubletemp=255/log(256);

//cout"doubledoubletemp="tempendl;

Matimage=imread("C://Users//TOPSUN//Desktop//2.jpg",1);

if(!image.data)

cout"imageloadingerror"endl;

return-1;

imshow("原