Iphone 如何模糊图像，但保留锐利的对象边界？

我想对UIImage执行“智能”模糊，其中内容模糊，但边缘保持锐利

例如，以下是我的原始图像：

下面是我希望在应用模糊后看到的：

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如何在UIImage上进行这样的“智能”模糊？

您在这里寻找的模糊称为双边模糊。与标准高斯模糊不同，根据周围像素与中心像素的相似程度，使用中心像素颜色平均周围像素的颜色。这会模糊对象的内部区域，但保留清晰的轮廓

在我的开源框架中，我有一个过滤器来实现这一点，称为GPUImageBilateralFilter。这是应用于图像时的输出（使用blurSize 1.0和distanceNormalizationFactor 1.6）：

在我的结果和你的目标之间有一些细微的差别，但这可能是由于我使用的特定权重。通过调整这里的参数，您应该能够更接近上面的内容

OpenCV也有双边模糊过滤器，如果您想在这个框架之外使用它，您可以将源代码带到我的片段着色器并使用它来构建自己的OpenGL ES实现：

 uniform sampler2D inputImageTexture;

 const lowp int GAUSSIAN_SAMPLES = 9;

 varying highp vec2 textureCoordinate;
 varying highp vec2 blurCoordinates[GAUSSIAN_SAMPLES];

 uniform mediump float distanceNormalizationFactor;

 void main()
 {
     lowp vec4 centralColor;
     lowp float gaussianWeightTotal;
     lowp vec4 sum;
     lowp vec4 sampleColor;
     lowp float distanceFromCentralColor;
     lowp float gaussianWeight;

     centralColor = texture2D(inputImageTexture, blurCoordinates[4]);
     gaussianWeightTotal = 0.18;
     sum = centralColor * 0.18;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[0]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.05 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[1]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.09 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[2]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.12 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[3]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.15 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[5]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.15 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[6]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.12 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[7]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.09 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[8]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.05 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     gl_FragColor = sum / gaussianWeightTotal;
 }

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你在这里寻找的模糊称为双边模糊。与标准高斯模糊不同，根据周围像素与中心像素的相似程度，使用中心像素颜色平均周围像素的颜色。这会模糊对象的内部区域，但保留清晰的轮廓

在我的开源框架中，我有一个过滤器来实现这一点，称为GPUImageBilateralFilter。这是应用于图像时的输出（使用blurSize 1.0和distanceNormalizationFactor 1.6）：

在我的结果和你的目标之间有一些细微的差别，但这可能是由于我使用的特定权重。通过调整这里的参数，您应该能够更接近上面的内容

OpenCV也有双边模糊过滤器，如果您想在这个框架之外使用它，您可以将源代码带到我的片段着色器并使用它来构建自己的OpenGL ES实现：

 uniform sampler2D inputImageTexture;

 const lowp int GAUSSIAN_SAMPLES = 9;

 varying highp vec2 textureCoordinate;
 varying highp vec2 blurCoordinates[GAUSSIAN_SAMPLES];

 uniform mediump float distanceNormalizationFactor;

 void main()
 {
     lowp vec4 centralColor;
     lowp float gaussianWeightTotal;
     lowp vec4 sum;
     lowp vec4 sampleColor;
     lowp float distanceFromCentralColor;
     lowp float gaussianWeight;

     centralColor = texture2D(inputImageTexture, blurCoordinates[4]);
     gaussianWeightTotal = 0.18;
     sum = centralColor * 0.18;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[0]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.05 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[1]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.09 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[2]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.12 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[3]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.15 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[5]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.15 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[6]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.12 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[7]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.09 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     sampleColor = texture2D(inputImageTexture, blurCoordinates[8]);
     distanceFromCentralColor = min(distance(centralColor, sampleColor) * distanceNormalizationFactor, 1.0);
     gaussianWeight = 0.05 * (1.0 - distanceFromCentralColor);
     gaussianWeightTotal += gaussianWeight;
     sum += sampleColor * gaussianWeight;

     gl_FragColor = sum / gaussianWeightTotal;
 }

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回答得很好。喜欢包含开源项目和示例代码。@Brad Larson:我可以单独对图像的特定部分应用过滤效果吗？假设我的图像宽度为320，则不适用于整个图像。所以，我想将滤波效果从60像素增加到70像素，然后仅从200像素增加到220像素。因此，过滤效果不会应用于整个系统image@Brad拉森：+1谢谢，这非常有帮助：D我用它“升级”了一个高斯模糊着色器；我发现效果相当微妙，除非我将原始除数保留在最后一行（不通过与中心颜色的距离进行变换）。不过需要注意的是，虽然边缘更清晰，但有点褪色。答案很好。喜欢包含开源项目和示例代码。@Brad Larson:我可以单独对图像的特定部分应用过滤效果吗？假设我的图像宽度为320，则不适用于整个图像。所以，我想将滤波效果从60像素增加到70像素，然后仅从200像素增加到220像素。因此，过滤效果不会应用于整个系统image@Brad拉森：+1谢谢，这非常有帮助：D我用它“升级”了一个高斯模糊着色器；我发现效果相当微妙，除非我将原始除数保留在最后一行（不通过与中心颜色的距离进行变换）。不过值得注意的是，虽然边缘更清晰，但它们有点褪色。