在 JAVA 中，我试图以编程方式判断 2 张图像在屏幕上显示时是否相等（即相同的图像，即使它们具有不同的色彩空间。是否有一段代码在呈现 2 张图像时会返回布尔值？
我的例子之一是我转换为灰度 PNG 的 RGB PNG。两张图片看起来一样，我想以编程方式证明这一点。另一个例子是两个图像，它们在屏幕上显示完全相同的颜色像素，但用于 100% 透明像素的颜色发生了变化。
问问题
17129 次
5 回答
4
我查看了所有解决方案，并确定它们可以告诉您图像对于某些类型的图像有多么不同或适用于某些类型的图像，但不是全部。这是我想出的解决方案...
package image.utils;
import java.awt.Graphics2D;
import java.awt.Image;
import java.awt.Toolkit;
import java.awt.color.ColorSpace;
import java.awt.image.BufferedImage;
import java.awt.image.ColorConvertOp;
import java.awt.image.PixelGrabber;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import javax.imageio.ImageIO;
import javax.imageio.ImageReader;
import javax.imageio.stream.ImageInputStream;
import javax.swing.ImageIcon;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* Utility methods used to interact with images.
*/
public class ImageUtils {
private final static Logger logger = LoggerFactory.getLogger(ImageUtils.class);
private static final boolean equals(final int[] data1, final int[] data2) {
final int length = data1.length;
if (length != data2.length) {
logger.debug("File lengths are different.");
return false;
}
for(int i = 0; i < length; i++) {
if(data1[i] != data2[i]) {
//If the alpha is 0 for both that means that the pixels are 100%
//transparent and the color does not matter. Return false if
//only 1 is 100% transparent.
if((((data1[i] >> 24) & 0xff) == 0) && (((data2[i] >> 24) & 0xff) == 0)) {
logger.debug("Both pixles at spot {} are different but 100% transparent.", Integer.valueOf(i));
} else {
logger.debug("The pixel {} is different.", Integer.valueOf(i));
return false;
}
}
}
logger.debug("Both groups of pixels are the same.");
return true;
}
private static final int[] getPixels(final BufferedImage img, final File file) {
final int width = img.getWidth();
final int height = img.getHeight();
int[] pixelData = new int[width * height];
final Image pixelImg;
if (img.getColorModel().getColorSpace() == ColorSpace.getInstance(ColorSpace.CS_sRGB)) {
pixelImg = img;
} else {
pixelImg = new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_sRGB), null).filter(img, null);
}
final PixelGrabber pg = new PixelGrabber(pixelImg, 0, 0, width, height, pixelData, 0, width);
try {
if(!pg.grabPixels()) {
throw new RuntimeException();
}
} catch (final InterruptedException ie) {
throw new RuntimeException(file.getPath(), ie);
}
return pixelData;
}
/**
* Gets the {@link BufferedImage} from the passed in {@link File}.
*
* @param file The <code>File</code> to use.
* @return The resulting <code>BufferedImage</code>
*/
@SuppressWarnings("unused")
final static BufferedImage getBufferedImage(final File file) {
Image image;
try (final FileInputStream inputStream = new FileInputStream(file)) {
// ImageIO.read(file) is broken for some images so I went this
// route
image = Toolkit.getDefaultToolkit().createImage(file.getCanonicalPath());
//forces the image to be rendered
new ImageIcon(image);
} catch(final Exception e2) {
throw new RuntimeException(file.getPath(), e2);
}
final BufferedImage converted = new BufferedImage(image.getWidth(null), image.getHeight(null), BufferedImage.TYPE_INT_ARGB);
final Graphics2D g2d = converted.createGraphics();
g2d.drawImage(image, 0, 0, null);
g2d.dispose();
return converted;
}
/**
* Compares file1 to file2 to see if they are the same based on a visual
* pixel by pixel comparison. This has issues with marking images different
* when they are not. Works perfectly for all images.
*
* @param file1 First file to compare
* @param file2 Second image to compare
* @return <code>true</code> if they are equal, otherwise
* <code>false</code>.
*/
private final static boolean visuallyCompareJava(final File file1, final File file2) {
return equals(getPixels(getBufferedImage(file1), file1), getPixels(getBufferedImage(file2), file2));
}
/**
* Compares file1 to file2 to see if they are the same based on a visual
* pixel by pixel comparison. This has issues with marking images different
* when they are not. Works perfectly for all images.
*
* @param file1 Image 1 to compare
* @param file2 Image 2 to compare
* @return <code>true</code> if both images are visually the same.
*/
public final static boolean visuallyCompare(final File file1, final File file2) {
logger.debug("Start comparing \"{}\" and \"{}\".", file1.getPath(), file2.getPath());
if(file1 == file2) {
return true;
}
boolean answer = visuallyCompareJava(file1, file2);
if(!answer) {
logger.info("The files \"{}\" and \"{}\" are not pixel by pixel the same image. Manual comparison required.", file1.getPath(), file2.getPath());
}
logger.debug("Finish comparing \"{}\" and \"{}\".", file1.getPath(), file2.getPath());
return answer;
}
/**
* @param file The image to check
* @return <code>true</code> if the image contains one or more pixels with
* some percentage of transparency (Alpha)
*/
public final static boolean containsAlphaTransparency(final File file) {
logger.debug("Start Alpha pixel check for {}.", file.getPath());
boolean answer = false;
for(final int pixel : getPixels(getBufferedImage(file), file)) {
//If the alpha is 0 for both that means that the pixels are 100%
//transparent and the color does not matter. Return false if
//only 1 is 100% transparent.
if(((pixel >> 24) & 0xff) != 255) {
logger.debug("The image contains Aplha Transparency.");
return true;
}
}
logger.debug("The image does not contain Aplha Transparency.");
logger.debug("End Alpha pixel check for {}.", file.getPath());
return answer;
}
}
于 2014-07-02T03:07:37.747 回答
4
对于灰度图像，我使用均方误差来衡量两个图像之前的差异程度。只需将每个图像中的相应像素插入公式即可。
这不仅可以告诉您它们是否完全相同，还可以告诉您两个图像的不同之处，尽管方式相当粗略。
https://en.wikipedia.org/wiki/Mean_squared_error
编辑：
注意：这是 C# 代码而不是 Java（抱歉，但这是我最初写的），但是它应该很容易转移。
//Calculates the MSE between two images
private double MSE(Bitmap original, Bitmap enhanced)
{
Size imgSize = original.Size;
double total = 0;
for (int y = 0; y < imgSize.Height; y++)
{
for (int x = 0; x < imgSize.Width; x++)
{
total += System.Math.Pow(original.GetPixel(x, y).R - enhanced.GetPixel(x, y).R, 2);
}
}
return (total / (imgSize.Width * imgSize.Height));
}
于 2013-05-17T07:10:38.780 回答
2
于 2013-05-17T06:35:30.277 回答
1
如果您的意思完全相同，请比较每个像素。
如果你的意思是比较 RGB 图像和灰度图像，你需要先将 RGB 转换为灰度，为此，你需要知道你之前是如何做 RGB->Greyscale 的，有不同的方法可以做到这一点，你可以得到不同的结果。
编辑，如果它在 RGB->Greyscale 中使用的方法是 liner，您可以grey = a*R + b*G + c*B通过比较 3 个像素来计算公式中的 a、b、c。
于 2013-05-17T06:33:22.053 回答
0
我尝试过的最简单的方法之一是获取两个图像的像素数组并将它们与 Arrays.equals 方法进行比较。代码示例：
package image_processing;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
import java.util.Arrays;
import javax.imageio.ImageIO;
public class CheckPixels {
public static void main(String args[]) throws IOException {
File pic1 = new File("D:\\ani\\img1.png");
File pic2 = new File("D:\\ani\\img2.png");
if (Arrays.equals(returnPixelVal(pic1), returnPixelVal(pic2))) {
System.out.println("Match");
} else {
System.out.println("No match");
}
}
public static byte[] returnPixelVal(File in) {
BufferedImage img = null;
File f = null;
byte[] pixels = null;
// read image
try {
f = in;
img = ImageIO.read(f);
pixels = ((DataBufferByte) img.getRaster().getDataBuffer()).getData();
} catch (IOException e) {
System.out.println(e);
}
return pixels;
}
}
于 2017-09-12T11:28:04.017 回答