Processes the loaded pixels. This method is called back every time when a new portion of pixels is loaded.
* * * @param pixelsRectangle The pixels rectangle. * @param pixels The 32-bit ARGB pixels. * @param start The start pixels point. * @param end The end pixels point. */ public void process(com.aspose.imaging.Rectangle pixelsRectangle, int[] pixels, com.aspose.imaging.Point start, com.aspose.imaging.Point end) { for (int pixel : pixels) { int alpha = (pixel >> 24) & 0xff; if (alpha == 0) { this.count++; } } } } // 以下是使用计数器的示例。 com.aspose.imaging.Image image = com.aspose.imaging.Image.load("c:\\temp\\alpha.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 创建 com.aspose.imaging.IPartialArgb32PixelLoader 的实例并将其传递给 com.aspose.imaging.RasterImage.LoadPartialArgb32Pixels。 TransparentArgb32PixelCounter counter = new TransparentArgb32PixelCounter(); // 加载整幅图像的像素。图像的任意矩形区域都可以作为 com.aspose.imaging.RasterImage.loadPartialArgb32Pixels 方法的第一个参数指定。 rasterImage.loadPartialArgb32Pixels(rasterImage.getBounds(), counter); System.out.println("The number of fully transparent pixels is " + counter.getCount()); System.out.println("The total number of pixels is " + (image.getWidth() * image.getHeight())); } finally { image.dispose(); } // 输出可能如下所示： // 完全透明像素的数量为 55157。 // 像素的总数量为 120400。 ``` ### loadPartialPixels(Rectangle desiredRectangle, IPartialPixelLoader pixelLoader) {#loadPartialPixels-com.aspose.imaging.Rectangle-com.aspose.imaging.IPartialPixelLoader-} ``` public void loadPartialPixels(Rectangle desiredRectangle, IPartialPixelLoader pixelLoader) ``` 按包部分加载像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | desiredRectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 所需的矩形。 | | pixelLoader | [IPartialPixelLoader](../../com.aspose.imaging/ipartialpixelloader) | 像素加载器。 | **Example: The following example shows how to load and process pixels of a raster image using your own partial processor.** 下面的示例展示了如何使用您自己的部分处理器加载和处理光栅图像的像素。例如，考虑一个统计图像中完全透明像素的问题。为了使用部分加载机制统计透明像素，介绍了一个实现 com.aspose.imaging.IPartialPixelLoader 的单独类 TransparentPixelCounter。 ``` java // 首先，实现 com.aspose.imaging.IPartialPixelLoader 来统计所有完全透明的像素。 /** Counts the number of fully transparent pixels with alpha channel value of 0. */ class TransparentPixelCounter implements com.aspose.imaging.IPartialPixelLoader { /** * The number of fully transparent pixels. */ private int count; /** * Gets the number of fully transparent pixels. */ public int getCount() { return this.count; } /** *Processes the loaded pixels. This method is called back every time when a new portion of pixels is loaded.
* * @param pixelsRectangle The pixels rectangle. * @param pixels The 32-bit ARGB pixels. * @param start The start pixels point. * @param end The end pixels point. */ public void process(com.aspose.imaging.Rectangle pixelsRectangle, com.aspose.imaging.Color[] pixels, com.aspose.imaging.Point start, com.aspose.imaging.Point end) { for (com.aspose.imaging.Color pixel : pixels) { if (pixel.getA() == 0) { this.count++; } } } } // 以下是使用计数器的示例。 com.aspose.imaging.Image image = com.aspose.imaging.Image.load("c:\\temp\\alpha.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 创建 com.aspose.imaging.IPartialPixelLoader 的实例并将其传递给 com.aspose.imaging.RasterImage.loadPartialPixels。 TransparentPixelCounter counter = new TransparentPixelCounter(); // 加载整幅图像的像素。图像的任意矩形区域都可以作为 com.aspose.imaging.RasterImage.loadPartialPixels 方法的第一个参数指定。 rasterImage.loadPartialPixels(rasterImage.getBounds(), counter); System.out.println("The number of fully transparent pixels is " + counter.getCount()); System.out.println("The total number of pixels is " + (image.getWidth() * image.getHeight())); } finally { image.dispose(); } // 输出可能如下所示： // 完全透明像素的数量为 55157。 // 像素的总数量为 120400。 ``` ### loadArgb32Pixels(Rectangle rectangle) {#loadArgb32Pixels-com.aspose.imaging.Rectangle-} ``` public int[] loadArgb32Pixels(Rectangle rectangle) ``` 加载 32 位 ARGB 像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要从中加载像素的矩形。 | **Returns:** int[] - 已加载的 32 位 ARGB 像素数组。 **Example: The following example shows how to load and process pixels of a raster image.** 下面的示例展示了如何加载和处理光栅图像的像素。像素以 32 位整数值表示。例如，考虑一个统计图像中完全透明像素的问题。 ``` java com.aspose.imaging.Image image = com.aspose.imaging.Image.load("c:\\temp\\alpha.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 加载整幅图像的像素。图像的任意矩形区域都可以作为 com.aspose.imaging.RasterImage.loadArgb32Pixels 方法的参数指定。 int[] pixels = rasterImage.loadArgb32Pixels(rasterImage.getBounds()); int count = 0; for (int pixel : pixels) { int alpha = (pixel >> 24) & 0xff; if (alpha == 0) { count++; } } System.out.println("The number of fully transparent pixels is " + count); System.out.println("The total number of pixels is " + (image.getWidth() * image.getHeight())); } finally { image.dispose(); } ``` ### loadArgb64Pixels(Rectangle rectangle) {#loadArgb64Pixels-com.aspose.imaging.Rectangle-} ``` public long[] loadArgb64Pixels(Rectangle rectangle) ``` 加载 64 位 ARGB 像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要从中加载像素的矩形。 | **Returns:** long[] - 已加载的 64 位 ARGB 像素数组。 **Example: The following example shows how to load and process pixels of a raster image.** 下面的示例展示了如何加载和处理光栅图像的像素。像素以 64 位整数值表示。例如，考虑一个统计图像中完全透明像素的问题。 ``` java com.aspose.imaging.Image image = com.aspose.imaging.Image.load("c:\\temp\\16rgba.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 加载整幅图像的像素。图像的任意矩形区域都可以作为 com.aspose.imaging.RasterImage.loadArgb64Pixels 方法的参数指定。 // 请注意，图像本身必须每个样本为 16 位，因为 com.aspose.imaging.RasterImage.loadArgb64Pixels 不支持每个样本为 8 位的情况。 // 若要使用每个样本为 8 位，请使用传统的 com.aspose.imaging.RasterImage.loadArgb32Pixels 方法。 long[] pixels = rasterImage.loadArgb64Pixels(rasterImage.getBounds()); int count = 0; for (long pixel : pixels) { // 请注意，所有颜色分量（包括 alpha）均以 16 位值表示，因此其允许的取值范围为 [0, 63535]。 long alpha = (pixel >> 48) & 0xffff; if (alpha == 0) { count++; } } System.out.println("The number of fully transparent pixels is " + count); System.out.println("The total number of pixels is " + (image.getWidth() * image.getHeight())); } finally { image.dispose(); } ``` ### loadPartialArgb64Pixels(Rectangle rectangle, IPartialArgb64PixelLoader partialPixelLoader) {#loadPartialArgb64Pixels-com.aspose.imaging.Rectangle-com.aspose.imaging.IPartialArgb64PixelLoader-} ``` public final void loadPartialArgb64Pixels(Rectangle rectangle, IPartialArgb64PixelLoader partialPixelLoader) ``` 按包部分加载 64 位 ARGB 像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 所需的矩形。 | | partialPixelLoader | [IPartialArgb64PixelLoader](../../com.aspose.imaging/ipartialargb64pixelloader) | 64 位 ARGB 像素加载器。 | ### loadPixels(Rectangle rectangle) {#loadPixels-com.aspose.imaging.Rectangle-} ``` public Color[] loadPixels(Rectangle rectangle) ``` 加载像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要从中加载像素的矩形。 | **Returns:** com.aspose.imaging.Color[] - 已加载的像素数组。 **Example: The following example shows how to load and process pixels of a raster image.** 下面的示例展示了如何加载和处理光栅图像的像素。例如，考虑一个统计图像中完全透明像素的问题。 ``` java com.aspose.imaging.Image image = com.aspose.imaging.Image.load("c:\\temp\\alpha.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 加载整个图像的像素。图像的任意矩形区域可以作为 Aspose.Imaging.RasterImage.LoadPixels 方法的参数指定。 com.aspose.imaging.Color[] pixels = rasterImage.loadPixels(rasterImage.getBounds()); int count = 0; for (com.aspose.imaging.Color pixel : pixels) { if (pixel.getA() == 0) { count++; } } System.out.println("The number of fully transparent pixels is " + count); System.out.println("The total number of pixels is " + (image.getWidth() * image.getHeight())); } finally { image.dispose(); } ``` ### loadCmykPixels(Rectangle rectangle) {#loadCmykPixels-com.aspose.imaging.Rectangle-} ``` public CmykColor[] loadCmykPixels(Rectangle rectangle) ``` 以 CMYK 格式加载像素。此方法已弃用。请使用更有效的 `loadCmyk32Pixels(Rectangle)` 方法。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要从中加载像素的矩形。 | **Returns:** com.aspose.imaging.CmykColor[] - 已加载的 CMYK 像素数组。 ### loadCmyk32Pixels(Rectangle rectangle) {#loadCmyk32Pixels-com.aspose.imaging.Rectangle-} ``` public int[] loadCmyk32Pixels(Rectangle rectangle) ``` 以 CMYK 格式加载像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要从中加载像素的矩形。 | **Returns:** int[] - 已加载的 CMYK 像素以 32 位整数值的形式呈现。 ### loadRawData(Rectangle rectangle, RawDataSettings rawDataSettings, IPartialRawDataLoader rawDataLoader) {#loadRawData-com.aspose.imaging.Rectangle-com.aspose.imaging.RawDataSettings-com.aspose.imaging.IPartialRawDataLoader-} ``` public void loadRawData(Rectangle rectangle, RawDataSettings rawDataSettings, IPartialRawDataLoader rawDataLoader) ``` 使用部分处理机制加载原始图像数据。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要从中加载数据的图像所需矩形区域。 | | rawDataSettings | [RawDataSettings](../../com.aspose.imaging/rawdatasettings) | 原始数据设置。 | | rawDataLoader | [IPartialRawDataLoader](../../com.aspose.imaging/ipartialrawdataloader) | 原始数据加载器。 | **Example: The following example shows how to extract pixels from the raw image data using RawDataSettings.** 以下示例展示了如何使用 RawDataSettings 从原始图像数据中提取像素。例如，考虑统计图像中完全透明像素的问题。 ``` java // 首先，实现一个计数器。对于原始数据，计数器可能如下所示： /** Counts the number of fully transparent pixels with alpha channel value of 0. */ class TransparentPixelRawDataCounter implements com.aspose.imaging.IPartialRawDataLoader { /** * The number of fully transparent pixels. */ private int count; /** * The raw data settings of the loaded image. */ private com.aspose.imaging.RawDataSettings rawDataSettings; /** * Gets the number of fully transparent pixels. */ public int getCount() { return this.count; } /** *Initializes a new instance of the
Processes the loaded raw data. This method is called back every time when a new portion of raw data is loaded.
* * @param dataRectangle The raw data rectangle. * @param data The raw data. * @param start The start data point. * @param end The end data point. */ public void process(com.aspose.imaging.Rectangle dataRectangle, byte[] data, com.aspose.imaging.Point start, com.aspose.imaging.Point end)// throws java.lang.Exception { int[] channelBits = this.rawDataSettings.getPixelDataFormat().getChannelBits(); // 这里仅考虑简单格式，以简化代码。 // 我们只考虑每个样本为 8 位的图像。 for (int i = 0; i < channelBits.length; i++) { if (channelBits[i] != 8) { throw new java.lang.UnsupportedOperationException(); } } switch (this.rawDataSettings.getPixelDataFormat().getPixelFormat()) { case com.aspose.imaging.PixelFormat.Rgb: case com.aspose.imaging.PixelFormat.Bgr: { if (channelBits.length == 4) { // ARGB for (int i = 0; i < data.length; i += 4) { // Alpha 通道存储在最后，位于颜色分量之后。 if (data[i + 3] == 0) { this.count++; } } } } break; case com.aspose.imaging.PixelFormat.Grayscale: { if (channelBits.length == 2) { // 灰度 Alpha for (int i = 0; i < data.length; i += 2) { // Alpha 通道存储在最后，位于颜色分量之后。 if (data[i + 1] == 0) { this.count++; } } } } break; default: throw new java.lang.IllegalArgumentException("PixelFormat"); } } /** *Processes the loaded raw data. This method is called back every time when a new portion of raw data is loaded.
* * * @param dataRectangle The raw data rectangle. * @param data The raw data. * @param start The start data point. * @param end The end data point. * @param loadOptions The load options. */ public void process(com.aspose.imaging.Rectangle dataRectangle, byte[] data, com.aspose.imaging.Point start, com.aspose.imaging.Point end, com.aspose.imaging.LoadOptions loadOptions) { this.process(dataRectangle, data, start, end); } } // 以下是使用计数器的主要示例 com.aspose.imaging.Image image = com.aspose.imaging.Image.load("c:\\temp\\alpha.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; com.aspose.imaging.RawDataSettings settings = rasterImage.getRawDataSettings(); TransparentPixelRawDataCounter rawDataLoader = new TransparentPixelRawDataCounter(settings); // 加载整个图像的像素。图像的任意矩形区域可以作为 Aspose.Imaging.RasterImage.LoadRawData 方法的参数指定。 rasterImage.loadRawData(rasterImage.getBounds(), settings, rawDataLoader); System.out.println("The number of fully transparent pixels is " + rawDataLoader.getCount()); System.out.println("The total number of pixels is " + (image.getWidth() * image.getHeight())); } finally { image.dispose(); } // 输出可能如下所示： // 完全透明像素的数量为 55157。 // 像素的总数量为 120400。 ``` ### loadRawData(Rectangle rectangle, Rectangle dstImageBounds, RawDataSettings rawDataSettings, IPartialRawDataLoader rawDataLoader) {#loadRawData-com.aspose.imaging.Rectangle-com.aspose.imaging.Rectangle-com.aspose.imaging.RawDataSettings-com.aspose.imaging.IPartialRawDataLoader-} ``` public void loadRawData(Rectangle rectangle, Rectangle dstImageBounds, RawDataSettings rawDataSettings, IPartialRawDataLoader rawDataLoader) ``` 加载原始数据。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要从中加载原始数据的矩形。 | | dstImageBounds | [Rectangle](../../com.aspose.imaging/rectangle) | 目标图像的边界。 | | rawDataSettings | [RawDataSettings](../../com.aspose.imaging/rawdatasettings) | 用于已加载数据的原始数据设置。请注意，如果数据不是指定的格式，则会执行数据转换。 | | rawDataLoader | [IPartialRawDataLoader](../../com.aspose.imaging/ipartialrawdataloader) | 原始数据加载器。 | ### saveRawData(byte[] data, int dataOffset, Rectangle rectangle, RawDataSettings rawDataSettings) {#saveRawData-byte---int-com.aspose.imaging.Rectangle-com.aspose.imaging.RawDataSettings-} ``` public void saveRawData(byte[] data, int dataOffset, Rectangle rectangle, RawDataSettings rawDataSettings) ``` 保存原始数据。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | 数据 | byte[] | 原始数据。 | | dataOffset | int | 起始原始数据偏移量。 | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 原始数据矩形。 | | rawDataSettings | [RawDataSettings](../../com.aspose.imaging/rawdatasettings) | 数据所在的原始数据设置。 | ### saveArgb32Pixels(Rectangle rectangle, int[] pixels) {#saveArgb32Pixels-com.aspose.imaging.Rectangle-int---} ``` public void saveArgb32Pixels(Rectangle rectangle, int[] pixels) ``` 保存 32 位 ARGB 像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要保存像素的矩形。 | | 像素 | int[] | 32 位 ARGB 像素数组。 | **Example: The following example fills the central area of a raster image with black pixels using the com.** 下面的示例使用 com.aspose.imaging.RasterImage.saveArgb32Pixels 方法，用黑色像素填充光栅图像的中心区域。 ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 黑色方块 int[] pixels = new int[(rasterImage.getWidth() / 2) * (rasterImage.getHeight() / 2)]; for (int i = 0; i < pixels.length; i++) { pixels[i] = com.aspose.imaging.Color.getBlack().toArgb(); } // 在图像中心绘制黑色方块。 com.aspose.imaging.Rectangle area = new com.aspose.imaging.Rectangle(rasterImage.getWidth() / 4, rasterImage.getHeight() / 4, rasterImage.getWidth() / 2, rasterImage.getHeight() / 2); rasterImage.saveArgb32Pixels(area, pixels); rasterImage.save(dir + "sample.SaveArgb32Pixels.png"); } finally { image.dispose(); } ``` ### savePixels(Rectangle rectangle, Color[] pixels) {#savePixels-com.aspose.imaging.Rectangle-com.aspose.imaging.Color---} ``` public void savePixels(Rectangle rectangle, Color[] pixels) ``` 保存像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要保存像素的矩形。 | | pixels | [Color\[\]](../../com.aspose.imaging/color) | 像素数组。 | **Example: The following example fills the central area of a raster image with black pixels using the com.** 下面的示例使用 com.aspose.imaging.RasterImage.savePixels 方法，用黑色像素填充光栅图像的中心区域。 ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 黑色方块 com.aspose.imaging.Color[] pixels = new com.aspose.imaging.Color[(rasterImage.getWidth() / 2) * (rasterImage.getHeight() / 2)]; for (int i = 0; i < pixels.length; i++) { pixels[i] = com.aspose.imaging.Color.getBlack(); } // 在图像中心绘制黑色方块。 com.aspose.imaging.Rectangle area = new com.aspose.imaging.Rectangle(rasterImage.getWidth() / 4, rasterImage.getHeight() / 4, rasterImage.getWidth() / 2, rasterImage.getHeight() / 2); rasterImage.savePixels(area, pixels); rasterImage.save(dir + "sample.SavePixels.png"); } finally { image.dispose(); } ``` ### toBitmap() {#toBitmap--} ``` public BufferedImage toBitmap() ``` 将光栅图像转换为位图。 **Returns:** java.awt.image.BufferedImage - 位图 **Example: The following example converts a BMP image to a native Java bitmap.** ``` java com.aspose.imaging.Image image = com.aspose.imaging.Image.load("c:\\temp\\sample.bmp"); try { com.aspose.imaging.fileformats.bmp.BmpImage bmpImage = (com.aspose.imaging.fileformats.bmp.BmpImage) image; java.awt.image.BufferedImage bitmap = bmpImage.toBitmap(); // 处理本机 Java 位图。 } finally { image.dispose(); } ``` ### saveCmykPixels(Rectangle rectangle, CmykColor[] pixels) {#saveCmykPixels-com.aspose.imaging.Rectangle-com.aspose.imaging.CmykColor---} ``` public void saveCmykPixels(Rectangle rectangle, CmykColor[] pixels) ``` 保存像素。此方法已弃用。请使用更有效的 `saveCmyk32Pixels(Rectangle, int[])` 方法。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要保存像素的矩形。 | | pixels | [CmykColor\[\]](../../com.aspose.imaging/cmykcolor) | CMYK 像素数组。 | ### saveCmyk32Pixels(Rectangle rectangle, int[] pixels) {#saveCmyk32Pixels-com.aspose.imaging.Rectangle-int---} ``` public void saveCmyk32Pixels(Rectangle rectangle, int[] pixels) ``` 保存像素。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 要保存像素的矩形。 | | 像素 | int[] | CMYK 像素以 32 位整数值的形式呈现。 | **Example: The following example fills the central area of a raster image with black pixels using the com.** 下面的示例使用 com.aspose.imaging.RasterImage.saveCmyk32Pixels 方法，用黑色像素填充光栅图像的中心区域。 ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 获取 CMYK 颜色空间中黑色的整数表示。 int blackCmyk = com.aspose.imaging.CmykColorHelper.toCmyk(com.aspose.imaging.Color.getBlack()); // 黑色方块。 int[] pixels = new int[(rasterImage.getWidth() / 2) * (rasterImage.getHeight() / 2)]; for (int i = 0; i < pixels.length; i++) { pixels[i] = blackCmyk; } // 在图像中心绘制黑色方块。 com.aspose.imaging.Rectangle area = new com.aspose.imaging.Rectangle(rasterImage.getWidth() / 4, rasterImage.getHeight() / 4, rasterImage.getWidth() / 2, rasterImage.getHeight() / 2); rasterImage.saveCmyk32Pixels(area, pixels); rasterImage.save(dir + "sample.SaveCmyk32Pixels.png"); } finally { image.dispose(); } ``` ### setResolution(double dpiX, double dpiY) {#setResolution-double-double-} ``` public void setResolution(double dpiX, double dpiY) ``` 为此 `RasterImage` 设置分辨率。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | dpiX | double | `RasterImage` 的水平分辨率（每英寸点数）。 | | dpiY | double | `RasterImage` 的垂直分辨率（每英寸点数）。 | **Example: The following example shows how to set horizontal/vertical resolution of a raster image.** ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.jpg"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 获取图像的水平和垂直分辨率 double horizontalResolution = rasterImage.getHorizontalResolution(); double verticalResolution = rasterImage.getVerticalResolution(); System.out.println("The horizontal resolution, in pixels per inch: " + horizontalResolution); System.out.println("The vertical resolution, in pixels per inch: " + verticalResolution); if (horizontalResolution != 96.0 || verticalResolution != 96.0) { // 使用 SetResolution 方法在一次调用中更新两个分辨率值。 System.out.println("Set resolution values to 96 dpi"); rasterImage.setResolution(96.0, 96.0); System.out.println("The horizontal resolution, in pixels per inch: " + rasterImage.getHorizontalResolution()); System.out.println("The vertical resolution, in pixels per inch: " + rasterImage.getVerticalResolution()); } // 输出可能如下所示： // 水平分辨率，单位为每英寸像素：300.0 // 垂直分辨率，单位为每英寸像素：300.0 // 将分辨率值设置为 96 dpi // 水平分辨率，单位为每英寸像素：96.0 // 垂直分辨率，单位为每英寸像素：96.0 } finally { image.dispose(); } ``` ### setPalette(IColorPalette palette, boolean updateColors) {#setPalette-com.aspose.imaging.IColorPalette-boolean-} ``` public void setPalette(IColorPalette palette, boolean updateColors) ``` 设置图像调色板。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | palette | [IColorPalette](../../com.aspose.imaging/icolorpalette) | 要设置的调色板。 | | updateColors | boolean | 如果设置为 `true`，颜色将根据新调色板进行更新；否则颜色索引保持不变。请注意，如果某些索引没有对应的调色板条目，未更改的索引可能在加载时导致图像崩溃。 | ### autoRotate() {#autoRotate--} ``` public final void autoRotate() ``` 自动根据从 Exif 元数据提取的方向数据旋转图像。此方法确保图像以正确的方向显示，提升用户体验并消除手动调整的需求。通过分析 Exif 信息，图像会相应旋转，提供跨平台和设备的无缝观看体验。此自动旋转过程简化了图像处理，并在处理大量方向各异的图像时提升整体可用性。 ### resize(int newWidth, int newHeight, ImageResizeSettings settings) {#resize-int-int-com.aspose.imaging.ImageResizeSettings-} ``` public void resize(int newWidth, int newHeight, ImageResizeSettings settings) ``` 使用扩展选项调整图像大小。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | newWidth | int | 新的宽度。 | | newHeight | int | 新的高度。 | | settings | [ImageResizeSettings](../../com.aspose.imaging/imageresizesettings) | 调整大小的设置。 | ### rotate(float angle, boolean resizeProportionally, Color backgroundColor) {#rotate-float-boolean-com.aspose.imaging.Color-} ``` public void rotate(float angle, boolean resizeProportionally, Color backgroundColor) ``` 围绕中心旋转图像。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | angle | float | 旋转角度（以度为单位）。正值将顺时针旋转。 | | resizeProportionally | boolean | 如果设置为 `true`，图像尺寸将根据旋转矩形（角点）投影进行更改；否则保持尺寸不变，仅旋转内部图像内容。 | | backgroundColor | [Color](../../com.aspose.imaging/color) | 背景的颜色。 | ### rotate(float angle) {#rotate-float-} ``` public void rotate(float angle) ``` 围绕中心旋转图像。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | angle | float | 旋转角度（以度为单位）。正值将顺时针旋转。 | ### binarizeFixed(byte threshold) {#binarizeFixed-byte-} ``` public void binarizeFixed(byte threshold) ``` 使用预定义阈值对图像进行二值化 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | threshold | byte | 阈值。若像素的对应灰度值大于阈值，则赋值为 255，否则为 0。 | **Example: The following example binarizes a raster image with the predefined threshold.** 下面的示例使用预定义阈值对光栅图像进行二值化。二值化图像仅包含两种颜色——黑色和白色。 ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 使用阈值 127 对图像进行二值化。 // 如果像素的对应灰度值大于 127，则赋值为 255，否则为 0。 rasterImage.binarizeFixed((byte) 127); rasterImage.save(dir + "sample.BinarizeFixed.png"); } finally { image.dispose(); } ``` ### binarizeOtsu() {#binarizeOtsu--} ``` public void binarizeOtsu() ``` 使用 Otsu 阈值法对图像进行二值化 **Example: The following example binarizes a raster image with Otsu thresholding.** 下面的示例使用 Otsu 阈值法对光栅图像进行二值化。二值化图像仅包含两种颜色——黑色和白色。 ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 使用 Otsu 阈值法对图像进行二值化。 rasterImage.binarizeOtsu(); rasterImage.save(dir + "sample.BinarizeOtsu.png"); } finally { image.dispose(); } ``` ### binarizeBradley(double brightnessDifference) {#binarizeBradley-double-} ``` public void binarizeBradley(double brightnessDifference) ``` 使用 Bradley 的自适应阈值算法（基于积分图像阈值）对图像进行二值化 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | brightnessDifference | double | 像素的亮度差是该像素与以其为中心的 s × s 窗口像素平均值之间的差异。 | ### binarizeBradley(double brightnessDifference, int windowSize) {#binarizeBradley-double-int-} ``` public void binarizeBradley(double brightnessDifference, int windowSize) ``` 使用 Bradley 的自适应阈值算法（基于积分图像阈值）对图像进行二值化 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | brightnessDifference | double | 像素的亮度差是该像素与以其为中心的 s × s 窗口像素平均值之间的差异。 | | windowSize | int | 以该像素为中心的 s × s 窗口的大小 | **Example: The following example binarizes a raster image with Bradley's adaptive thresholding algorithm with the specified window size.** 下面的示例使用 Bradley 自适应阈值算法（指定窗口大小）对光栅图像进行二值化。二值化图像仅包含两种颜色——黑色和白色。 ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 使用亮度差 5 对图像进行二值化。亮度是指像素与以该像素为中心的 10×10 窗口像素平均值之间的差异。 rasterImage.binarizeBradley(5, 10); rasterImage.save(dir + "sample.BinarizeBradley5_10x10.png"); } finally { image.dispose(); } ``` ### blend(Point origin, RasterImage overlay, Rectangle overlayArea) {#blend-com.aspose.imaging.Point-com.aspose.imaging.RasterImage-com.aspose.imaging.Rectangle-} ``` public final void blend(Point origin, RasterImage overlay, Rectangle overlayArea) ``` 将此图像实例与 `overlay` 图像混合。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | origin | [Point](../../com.aspose.imaging/point) | 背景图像混合的原点。 | | overlay | [RasterImage](../../com.aspose.imaging/rasterimage) | 覆盖图像。 | | overlayArea | [Rectangle](../../com.aspose.imaging/rectangle) | 覆盖区域。 | ### blend(Point origin, RasterImage overlay, Rectangle overlayArea, byte overlayAlpha) {#blend-com.aspose.imaging.Point-com.aspose.imaging.RasterImage-com.aspose.imaging.Rectangle-byte-} ``` public void blend(Point origin, RasterImage overlay, Rectangle overlayArea, byte overlayAlpha) ``` 将此图像实例与 `overlay` 图像混合。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | origin | [Point](../../com.aspose.imaging/point) | 背景图像混合的原点。 | | overlay | [RasterImage](../../com.aspose.imaging/rasterimage) | 覆盖图像。 | | overlayArea | [Rectangle](../../com.aspose.imaging/rectangle) | 覆盖区域。 | | overlayAlpha | byte | 覆盖透明度。 | ### blend(Point origin, RasterImage overlay) {#blend-com.aspose.imaging.Point-com.aspose.imaging.RasterImage-} ``` public final void blend(Point origin, RasterImage overlay) ``` 将此图像实例与 `overlay` 进行混合，alpha == 255。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | origin | [Point](../../com.aspose.imaging/point) | 背景图像混合的原点。 | | overlay | [RasterImage](../../com.aspose.imaging/rasterimage) | 覆盖层。 | ### blend(Point origin, RasterImage overlay, byte overlayAlpha) {#blend-com.aspose.imaging.Point-com.aspose.imaging.RasterImage-byte-} ``` public final void blend(Point origin, RasterImage overlay, byte overlayAlpha) ``` 将此图像实例与 `overlay` 进行混合。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | origin | [Point](../../com.aspose.imaging/point) | 背景图像混合的原点。 | | overlay | [RasterImage](../../com.aspose.imaging/rasterimage) | 覆盖层。 | | overlayAlpha | byte | 覆盖透明度。 | ### grayscale() {#grayscale--} ``` public void grayscale() ``` 将图像转换为灰度表示 **Example: The following example transforms a colored raster image to its grayscale representation.** 下面的示例将彩色光栅图像转换为其灰度表示。灰度图像仅由灰色阴影组成，仅携带强度信息。 ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; rasterImage.grayscale(); rasterImage.save(dir + "sample.Grayscale.png"); } finally { image.dispose(); } ``` ### normalizeHistogram() {#normalizeHistogram--} ``` public void normalizeHistogram() ``` 归一化图像直方图 \\u2014 调整像素值以使用全部可用范围。 ### autoBrightnessContrast() {#autoBrightnessContrast--} ``` public void autoBrightnessContrast() ``` 对整幅图像进行自动自适应亮度和对比度归一化。 ### adjustBrightness(int brightness) {#adjustBrightness-int-} ``` public void adjustBrightness(int brightness) ``` 调整图像的亮度。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | brightness | int | 亮度值。 | **Example: The following example performs brightness correction of an image.** ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 设置亮度值。亮度的可接受范围为 [-255, 255]。 rasterImage.adjustBrightness(50); rasterImage.save(dir + "sample.AdjustBrightness.png"); } finally { image.dispose(); } ``` ### adjustContrast(float contrast) {#adjustContrast-float-} ``` public void adjustContrast(float contrast) ``` 图像对比度增强 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | contrast | float | 对比度值（范围为 [-100; 100]） | **Example: The following example performs contrast correction of an image.** ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 设置对比度值。对比度的可接受范围为 [-100f, 100f]。 rasterImage.adjustContrast(50); rasterImage.save(dir + "sample.AdjustContrast.png"); } finally { image.dispose(); } ``` ### embedDigitalSignature(String password) {#embedDigitalSignature-java.lang.String-} ``` public void embedDigitalSignature(String password) ``` 使用隐写技术将基于提供的密码的数字签名嵌入图像中。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | 密码 | java.lang.String | 用于生成数字签名数据的密码（最少4个字符）。 | **Example: The example shows how to embed digital signature based on provided password into image pixel data.** ``` java String imageFilePath = "ball.png"; String password = "veryStr0ngPassword"; try (Image image = Image.load(imageFilePath)) { image.embedDigitalSignature(password); image.save(outputPath); } ``` ### analyzePercentageDigitalSignature(String password) {#analyzePercentageDigitalSignature-java.lang.String-} ``` public int analyzePercentageDigitalSignature(String password) ``` 计算提取数据与原始密码之间的相似度百分比。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | 密码 | java.lang.String | 用于提取嵌入数据的密码。 | **Returns:** int - 百分比相似度值。 ### isDigitalSigned(String password) {#isDigitalSigned-java.lang.String-} ``` public boolean isDigitalSigned(String password) ``` 使用提供的密码和阈值快速检查图像是否已进行数字签名。 -------------------- 此方法通过利用 \#analyzePercentageDigitalSignature(String).analyzePercentageDigitalSignature(String) 提供最快的检测。一旦提取的数据达到指定阈值，旨在提高检测准确性的后续提取步骤将被跳过。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | 密码 | java.lang.String | 用于检查签名的密码。 | **Returns:** boolean - 如果图像已签名则为 true，否则为 false。 ### isDigitalSigned(String password, int percentageThreshold) {#isDigitalSigned-java.lang.String-int-} ``` public boolean isDigitalSigned(String password, int percentageThreshold) ``` 使用提供的密码和阈值快速检查图像是否已进行数字签名。 -------------------- 此方法通过利用 `GetSignPercentage` 提供最快的检测。一旦提取的数据达到指定阈值，后续旨在提高检测准确性的提取步骤将被跳过。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | 密码 | java.lang.String | 用于检查签名的密码。 | | percentageThreshold | int | 阈值（百分比）[0-100] 用于确定图像是否被视为已签名。如果未指定，将使用默认阈值（`75`）。 | **Returns:** boolean - 如果图像已签名则为 true，否则为 false。 ### adjustGamma(float gammaRed, float gammaGreen, float gammaBlue) {#adjustGamma-float-float-float-} ``` public void adjustGamma(float gammaRed, float gammaGreen, float gammaBlue) ``` 对图像进行伽马校正。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | gammaRed | float | 红色通道的伽马系数 | | gammaGreen | float | 绿色通道的伽马系数 | | gammaBlue | float | 蓝色通道系数的 Gamma | **Example: The following example performs gamma-correction of an image applying different coefficients for color components.** ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 为红色、绿色和蓝色通道设置各自的 Gamma 系数。 rasterImage.adjustGamma(1.5f, 2.5f, 3.5f); rasterImage.save(dir + "sample.AdjustGamma.png"); } finally { image.dispose(); } ``` ### adjustGamma(float gamma) {#adjustGamma-float-} ``` public void adjustGamma(float gamma) ``` 对图像进行伽马校正。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | 伽马 | float | 红色、绿色和蓝色通道系数的 Gamma | **Example: The following example performs gamma-correction of an image.** ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 为红色、绿色和蓝色通道设置 Gamma 系数。 rasterImage.adjustGamma(2.5f); rasterImage.save(dir + "sample.AdjustGamma.png"); } finally { image.dispose(); } ``` ### getSkewAngle() {#getSkewAngle--} ``` public final float getSkewAngle() ``` 获取倾斜角度。此方法适用于扫描的文本文件，用于在扫描时确定倾斜角度。 **Returns:** float - 倾斜角度，以度为单位。 ### normalizeAngle() {#normalizeAngle--} ``` public final void normalizeAngle() ``` 归一化角度。此方法适用于扫描的文本文件，以消除倾斜的扫描。此方法使用 \#getSkewAngle.getSkewAngle 和 [Image.rotate(float)](../../com.aspose.imaging/image\#rotate-float-) 方法。 ### normalizeAngle(boolean resizeProportionally, Color backgroundColor) {#normalizeAngle-boolean-com.aspose.imaging.Color-} ``` public void normalizeAngle(boolean resizeProportionally, Color backgroundColor) ``` 归一化角度。此方法适用于扫描的文本文件，以消除倾斜的扫描。此方法使用 \#getSkewAngle.getSkewAngle 和 \#rotate(float, boolean, Color).rotate(float, boolean, Color) 方法。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | resizeProportionally | boolean | 如果设置为 `true`，图像尺寸将根据旋转矩形（角点）投影进行更改；否则保持尺寸不变，仅旋转内部图像内容。 | | backgroundColor | [Color](../../com.aspose.imaging/color) | 背景的颜色。 | **Example: Skew is an artifact that might appear during document scanning process when the text/images of the document get rotated at a slight angle.** 倾斜是文档扫描过程中可能出现的伪影，当文档的文字/图像略微旋转时会产生。它可能由多种原因导致，但最常见的是扫描时纸张位置偏移。因此，去倾斜是检测并修复扫描文件（即位图）中此问题的过程，使去倾斜后的文档文字/图像正确且水平对齐。 ``` java String dir = "c:\\aspose.imaging\\issues\\java\\1461\\"; String inputFilePath = dir + "skewed.png"; String outputFilePath = dir + "skewed.out.png"; // 使用默认参数消除倾斜的扫描 com.aspose.imaging.RasterImage image = (com.aspose.imaging.RasterImage) com.aspose.imaging.Image.load(inputFilePath); try { // 去倾斜 image.normalizeAngle(false /*do not resize*/, com.aspose.imaging.Color.getLightGray() /*background color*/); image.save(outputFilePath); } finally { image.close(); } ``` ### filter(Rectangle rectangle, FilterOptionsBase options) {#filter-com.aspose.imaging.Rectangle-com.aspose.imaging.imagefilters.filteroptions.FilterOptionsBase-} ``` public void filter(Rectangle rectangle, FilterOptionsBase options) ``` 过滤指定的矩形。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | rectangle | [Rectangle](../../com.aspose.imaging/rectangle) | 矩形。 | | options | [FilterOptionsBase](../../com.aspose.imaging.imagefilters.filteroptions/filteroptionsbase) | 选项。 | **Example: The following example applies various types of filters to a raster image.** ``` java String dir = "c:\\temp\\"; com.aspose.imaging.Image image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 对整幅图像应用矩形大小为5的中值滤波器。 rasterImage.filter(rasterImage.getBounds(), new com.aspose.imaging.imagefilters.filteroptions.MedianFilterOptions(5)); rasterImage.save(dir + "sample.MedianFilter.png"); } finally { image.dispose(); } image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 对整幅图像应用核大小为5的双边平滑滤波器。 rasterImage.filter(rasterImage.getBounds(), new com.aspose.imaging.imagefilters.filteroptions.BilateralSmoothingFilterOptions(5)); rasterImage.save(dir + "sample.BilateralSmoothingFilter.png"); } finally { image.dispose(); } image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 对整幅图像应用半径为5、sigma值为4.0的高斯模糊滤波器。 rasterImage.filter(rasterImage.getBounds(), new com.aspose.imaging.imagefilters.filteroptions.GaussianBlurFilterOptions(5, 4.0)); rasterImage.save(dir + "sample.GaussianBlurFilter.png"); } finally { image.dispose(); } image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 对整幅图像应用半径为5、平滑值为4.0的Gauss-Wiener滤波器。 rasterImage.filter(rasterImage.getBounds(), new com.aspose.imaging.imagefilters.filteroptions.GaussWienerFilterOptions(5, 4.0)); rasterImage.save(dir + "sample.GaussWienerFilter.png"); } finally { image.dispose(); } image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 对整幅图像应用长度为5、平滑值为4.0、角度为90.0度的运动Wiener滤波器。 rasterImage.filter(rasterImage.getBounds(), new com.aspose.imaging.imagefilters.filteroptions.MotionWienerFilterOptions(10, 1.0, 90.0)); rasterImage.save(dir + "sample.MotionWienerFilter.png"); } finally { image.dispose(); } image = com.aspose.imaging.Image.load(dir + "sample.png"); try { com.aspose.imaging.RasterImage rasterImage = (com.aspose.imaging.RasterImage) image; // 对整幅图像应用核大小为5、sigma值为4.0的锐化滤波器。 rasterImage.filter(rasterImage.getBounds(), new com.aspose.imaging.imagefilters.filteroptions.SharpenFilterOptions(5, 4.0)); rasterImage.save(dir + "sample.SharpenFilter.png"); } finally { image.dispose(); } ``` ### replaceColor(Color oldColor, byte oldColorDiff, Color newColor) {#replaceColor-com.aspose.imaging.Color-byte-com.aspose.imaging.Color-} ``` public void replaceColor(Color oldColor, byte oldColorDiff, Color newColor) ``` 在允许的差异范围内将一种颜色替换为另一种颜色，并保留原始的 alpha 值以保持平滑边缘。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | oldColor | [Color](../../com.aspose.imaging/color) | 待替换的旧颜色。 | | oldColorDiff | byte | 允许的旧颜色差异，以便能够扩大替换后的颜色色调。 | | newColor | [Color](../../com.aspose.imaging/color) | 用于替换旧颜色的新颜色。 | ### replaceColor(int oldColorArgb, byte oldColorDiff, int newColorArgb) {#replaceColor-int-byte-int-} ``` public void replaceColor(int oldColorArgb, byte oldColorDiff, int newColorArgb) ``` 在允许的差异范围内将一种颜色替换为另一种颜色，并保留原始的 alpha 值以保持平滑边缘。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | oldColorArgb | int | 待替换的旧颜色 ARGB 值。 | | oldColorDiff | byte | 允许的旧颜色差异，以便能够扩大替换后的颜色色调。 | | newColorArgb | int | 用于替换旧颜色的新颜色 ARGB 值。 | ### replaceNonTransparentColors(Color newColor) {#replaceNonTransparentColors-com.aspose.imaging.Color-} ``` public void replaceNonTransparentColors(Color newColor) ``` 将所有非透明颜色替换为新颜色，并保留原始 alpha 值以保持平滑边缘。注意：如果在没有透明度的图像上使用，它会将所有颜色替换为单一颜色。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | newColor | [Color](../../com.aspose.imaging/color) | 用于替换非透明颜色的新颜色。 | ### replaceNonTransparentColors(int newColorArgb) {#replaceNonTransparentColors-int-} ``` public void replaceNonTransparentColors(int newColorArgb) ``` 将所有非透明颜色替换为新颜色，并保留原始 alpha 值以保持平滑边缘。注意：如果在没有透明度的图像上使用，它会将所有颜色替换为单一颜色。 **Parameters:** | 参数 | 类型 | 描述 | | --- | --- | --- | | newColorArgb | int | 用于替换非透明颜色的新颜色 ARGB 值。 |