来自 UIImage 的宝丽来滤镜 [英] polaroid filter from UIImage

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本文介绍了来自 UIImage 的宝丽来滤镜的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在尝试在 iphone 中实现一些图像过滤器,例如宝丽来.我搜索了如何过滤现有的 UIImage 以将其转换为 polaroid 样式并遇到这个 stackoverflow 链接.以那里的答案为起点,我遍历图像的每个像素,取RGB值,并将它们转换为HSV,到此为止我已经成功了.所以这就是我所做的(任何人都可以自由指出任何错误......)

I am trying to implement some image filters, like polaroid, in iphone. I searched on how to filter an existing UIImage to convert it into a polaroid style and come across this stackoverflow link. Taking the answer there as a starting point, I looped through each pixel of the image, taking RGB values, and converted them to HSV, up to this point I have been successful. So this is what I have done (anyone is free to point any mistakes..)

double minRGB(double r, double g, double b){
    if (r < g){
        if (r < b){
            return r;
        }else {
            return b;
        }
    }else { 
        if (g < b){
            return g;
        }else{
            return b;
        }
    }
}



double maxRGB(double r, double g, double b){
    if (r > g){
        if (r > b){
            return r;
        }else {
            return b;
        }
    }else { 
        if (g > b){
            return g;
        }else {
            return b;
        }
    }
}

void rgbToHsv(double redIn,double greenIn,double blueIn,double *hue,double *saturation,double* value){
    double min,max,delta;

    min                         =   minRGB(redIn,greenIn,blueIn);
    max                         =   maxRGB(redIn,greenIn,blueIn);
    *value                      =   max;
    delta                       =   max - min;
    if (max != 0) {
        *saturation             =   delta/max;
    }else {
        *saturation             =   0;
        *hue                        =   -1.0;
        return ;
    }
    if (redIn == max) {
        *hue                    =   (greenIn - blueIn)/delta;
    }else if (greenIn == max) {
        *hue                    =   2 + (blueIn - redIn)/delta;
    }else {
        *hue                    =   4 + (redIn - greenIn)/delta;
    }
    *hue                        *=  60.0;
    if (*hue < 0) {
        *hue                    +=  360.0;
    }
}

void hsvToRgb(double h,double s, double v, double *r,double *g, double *b){
    int i;
    float f, p, q, t;
    if( s == 0 ) {
        // achromatic (grey)
        *r = *g = *b = v;
        return;
    }
    h                           /=  60;         // sector 0 to 5
    i                           =   floor( h );
    f                           =   h - i;          // factorial part of h
    p                           =   v * ( 1 - s );
    q                           =   v * ( 1 - s * f );
    t                           =   v * ( 1 - s * ( 1 - f ) );
    switch( i ) {
        case 0:
            *r = v;
            *g = t;
            *b = p;
            break;
        case 1:
            *r = q;
            *g = v;
            *b = p;
            break;
        case 2:
            *r = p;
            *g = v;
            *b = t;
            break;
        case 3:
            *r = p;
            *g = q;
            *b = v;
            break;
        case 4:
            *r = t;
            *g = p;
            *b = v;
            break;
        default:        // case 5:
            *r = v;
            *g = p;
            *b = q;
            break;
    }
}


-(void)makeImagePolaroid:(UIImage*)myImage{
CGImageRef originalImage        =   [myImage CGImage];
CGColorSpaceRef colorSpace      =   CGColorSpaceCreateDeviceRGB();
CGContextRef bitmapContext      =   CGBitmapContextCreate(NULL,CGImageGetWidth(originalImage),CGImageGetHeight(originalImage),8,CGImageGetWidth(originalImage)*4,colorSpace,kCGImageAlphaPremultipliedLast);
CGColorSpaceRelease(colorSpace);
CGContextDrawImage(bitmapContext, CGRectMake(0, 0, CGBitmapContextGetWidth(bitmapContext), CGBitmapContextGetHeight(bitmapContext)), originalImage);
UInt8 *data                     =   CGBitmapContextGetData(bitmapContext);
int numComponents               =   4;
int bytesInContext              =   CGBitmapContextGetHeight(bitmapContext) * CGBitmapContextGetBytesPerRow(bitmapContext);
double redIn, greenIn, blueIn,alphaIn;
double hue,saturation,value;

for (int i = 0; i < bytesInContext; i += numComponents) {
    redIn                       =   (double)data[i]/255.0;
    greenIn                     =   (double)data[i+1]/255.0;
    blueIn                      =   (double)data[i+2]/255.0;
    alphaIn                     =   (double)data[i+3]/255.0;
    
    rgbToHsv(redIn,greenIn,blueIn,&hue,&saturation,&value);
    
    hue                         =   hue * 0.7;
    if (hue > 360) {
        hue                     =   360;
    }
    
    saturation                  =   saturation *1.3;
    if (saturation > 1.0) {
        saturation              =   1.0;
    }

    value                       =   value * 0.8;
    if (value > 1.0) {
        value                   =   1.0;
    }
    
    hsvToRgb(hue,saturation,value,&redIn,&greenIn,&blueIn);
    data[i]                     =   redIn * 255.0;
    data[i+1]                   =   greenIn * 255.0;
    data[i+2]                   =   blueIn * 255.0;
}
CGImageRef outImage             =   CGBitmapContextCreateImage(bitmapContext);
myImage                         =   [UIImage imageWithCGImage:outImage];
CGImageRelease(outImage);
return myImage;
}

现在我对图像处理的想法非常幼稚(甚至不是业余的).我阅读了 this 并尝试调整饱和度和色调,看看我是否可以获得宝丽来效果..我想我错过了一些东西,因为我得到了地球上除了宝丽来之外的所有效果(说我什么都没有).

Now my idea about image processing is very childish (not even amateurish). I read this and tried to adjust the saturation and hue to see if I can get a polaroid effect..I think I am missing something, for I got every effect on earth other than a polaroid (saying that I havent got anything)..

  1. 网络上是否有任何文件(或书籍)讲述图像筛选程序员点看法?(而不是设计师的观点没有photoshop的视图截图)
  2. 什么是色相、饱和度、值我必须在一个像素上做出改变这样我就可以拍成宝丽来了吗?
  3. 第三,我在正确的轨道上吗?

提前致谢..

推荐答案

这可能会有所帮助,来自 Camera+ 从 photoshop 中获取滤镜并为 iOS 复制它们.

This might be helpful, from Camera+ taking filters from photoshop and reproducing them for iOS.

http://taptaptap.com/blog/creating-a-camera-plus-fx/

这篇关于来自 UIImage 的宝丽来滤镜的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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