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    <p>Since you have access to matlab, I'd suggest digging into their code, assuming their image stuff is written in Matlab, which I think it is, and see how they convert RGB into intensity. Are they using HSL (Hue-Saturation-Luminance)? Or some other color conversion. Knowing that, you can find Java code to convert, for instance, RGB into HSL.</p> <p><strong>Edit:</strong><br> As per the comments on this question, I think this code will work. Its not complete as I didn't copy and re-write all the manipulation, but it should give you the idea.</p> <pre><code> import java.awt.image.BufferedImage; import java.io.File; import javax.imageio.ImageIO; public class Convolution { public static void main( String[] args ) throws Exception { File inputFile = new File("apple.jpg"); BufferedImage bufferedImage = ImageIO.read(inputFile); int w = bufferedImage.getWidth(); int h = bufferedImage.getHeight(); System.out.println("w=" + w + ", h=" + h); // Get Pixels int[] image = new int[w * h]; bufferedImage.getRGB(0, 0, w, h, image, 0, w); // Convert to simple grayscale for ( int y = 0; y &lt; h; y++ ) { for ( int x = 0; x &lt; w; x++ ) { int idx = ( y * w ) + x; int p = image[idx]; int r = p &amp; 0x00FF0000 &gt;&gt; 16; int g = p &amp; 0x0000FF &gt;&gt; 8; int b = p &amp; 0x000000FF; image[idx] = (int) ( ( r + g + b ) / 3.0 ); } } int convolutionSize = 3; int[][] convolution = { { 0, -1, 0 }, { -1, 4, -1 }, { 0, -1, 0 } }; int[] newImage = new int[w * h]; // Apply the convolution to the whole image, note that we start at // 1 instead 0 zero to avoid out-of-bounds access for ( int y = 1; y + 1 &lt; h; y++ ) { for ( int x = 1; x + 1 &lt; w; x++ ) { int idx = ( y * w ) + x; // Apply the convolution for ( int cy = 0; cy &lt; convolutionSize; cy++ ) { for ( int cx = 0; cx &lt; convolutionSize; cx++ ) { int cIdx = ( ( ( y - 1 ) + cy ) * w ) + ( ( x - 1 ) + cx ); newImage[idx] += convolution[cy][cx] * image[cIdx]; } } // pixel value rounding if ( newImage[idx] &lt; 0 ) { newImage[idx] = -newImage[idx]; } else { newImage[idx] = 0; } if ( newImage[idx] &gt; 0 ) { newImage[idx] = 120 - newImage[idx]; } else { newImage[idx] = 255; } } } // Convert to "proper" grayscale for ( int y = 0; y &lt; h; y++ ) { for ( int x = 0; x &lt; w; x++ ) { int idx = ( y * w ) + x; int p = newImage[idx]; newImage[idx] = 0xFF000000 | ( p &lt;&lt; 16 ) | ( p &lt;&lt; 8 ) | p; } } // Set the image to have the new values; bufferedImage.setRGB(0, 0, w, h, newImage, 0, w); // Write the new image as a PNG to avoid lossey compression, // and its eaiser than trying to display an image in Java. ImageIO.write(bufferedImage, "png", new File("new_apple.png")); } } </code></pre> <p><strong>Edit:</strong><br> Modified the code to work as expected. Its not fast, but it works.<br> Before:<br> <img src="https://i.stack.imgur.com/4B2kD.jpg" alt="Before"></p> <p>After:<br> <img src="https://i.stack.imgur.com/7lEcC.png" alt="After"></p>
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    1. COSome code: http://www.f4.fhtw-berlin.de/~barthel/ImageJ/ColorInspector//HTMLHelp/farbraumJava.htm
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    2. COThanks for the suggestion.i did so as u mentioned,but there seems no proper mention of Matlabs way of obtaining the intensity values. In java,the values which i get is a six to eight digit number and that too in negative number.i have tried various classes in java like Raster and Color classes but they werent useful enough.
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    3. COIs this a color or grayscale image? What format is it in, JPEG, GIF, ...? Could you give the code you are using to load image in matlab. I assume you are doing `A = imread(filename)` and then manipulating the matrix `A` directly. Is this correct?
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