Image Contrast and Grayscaling the Image in Java

Code First:

     public void contrastImage(BufferedImage img,float clip){//strecth luminance, adjust RGB proportionately

        int N=256;//bins

        makeHistogram(img,N);

        int height=img.getHeight();

        int width=img.getWidth();

        float min,max,sum=0,total=height*width;

        long index,mindex=0,maxdex=N;

        

        for(index=0;index<N;index++){

            sum+=hist[(int)index];

            if((mindex==0)&&((sum/total)>clip))     mindex=index;

            if((maxdex==N)&&((sum/total)>(1-clip))) maxdex=index-1;

        }

        min=255.0f*mindex/N;

        max=255.0f*maxdex/N;

        float scale;

        scale=(255.0f/(max-min));

        int result[][]=new int[width][height];

        for(int row=0;row<height;row++){

            for(int col=0;col<width;col++){

                result[col][row]=img.getRGB(col, row);

                Color c=new Color(result[col][row]);

                float red=c.getRed();

                float blue=c.getBlue();

                float green=c.getGreen();

                red=scale*(red-min);

                blue=scale*(blue-min);

                green=scale*(green-min);

                if(red>255)red=255;

                if(red<0)red=0;

                if(blue>255)blue=255;

                if(blue<0)blue=0;

                if(green>255)green=255;

                if(green<0)green=0;

                c=new Color((int)red,(int)green,(int)blue);

                img.setRGB(col,row,c.getRGB());

            }

        }

        

    }

Explanation:

     In processes where we need to contrast an image, the result is acquired by stretching the histogram curve, forming a comb-like graph. Thus, we first get the max and min intensities and then find the scale factor. Scaling is done for each color channel. 

The "clip" helps the user to change the amount of contrast. For example, 0.0025 means 25%. 

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Creating Image Histograms in Java

Why need histograms??

     Image histograms tell us a lot about their respective images. For example, a histogram with spaced lines tells us that its image has been previously scaled to contrast it. There will be a different post soon, that will tell you how important is the histograms. For now, we will see only, how to create histograms of images.

Extra software:

     Although you have ways to make histograms programmatically, but to reduce the effort for the learning process, you can rely on software that can show spreadsheets. I am using Microsoft Excel 2013.

The Code:

     int hist[];

     String Hist;

     public void makeHistogram(BufferedImage img,int bins){//woring on it

        int N=bins;

        hist=new int[N];

        for(int bright=0;bright<N;bright++)

            hist[bright]=0;

        

        int width=img.getWidth();

        int height=img.getHeight();

        int[][] result=new int[width][height];

        for(int row=0;row<height;row++){

            for(int col=0;col<width;col++){

                result[col][row]=img.getRGB(col, row);

                Color c=new Color(result[col][row]);

                int red=c.getRed();

                int blue=c.getBlue();

                int green=c.getGreen();

                int bright=(int)((red+blue+green)/3);

                int index=(int)((float)N*bright/bins);

                hist[index]++;

            }

        }

        for(int bright=0;bright<N;bright++){

            Hist=Hist+","+hist[bright];

        }

    }

In the code, the "bright" is calculated for each pixel, which is the average value of red, blue, and green values of the pixel. "bins" are nothing but defines the domain area of the histogram. It may be 256, 64, etc.

We are storing the array hist[] in String Hist, separated by commas. Contents in Hist then can be easily copied to a file. Such files be can easily analysed by these simple steps.

Here is an example:

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