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1. Convert Online
2. Image Converters
3. Blur Image

{
  "effect": "blur",
  "title": "Blur Image",
  "description": "You can use this Blur Image tool, to blur image(s). You can do for bulk number of images in one go, and also control the level of blur.",
  "multiple": true,
  "controls": [
    {
      "type": "range",
      "name": "sigma",
      "label": "Level of blur",
      "range": {
        "min": 1,
        "max": 10,
        "value": 2
      },
      "desc": "More the level of blur, more is the image blurred."
    }
  ],
  "content": "<h2>Blur Image Effect</h2>\n<p>The blur image effect smoothens an image by averaging the pixel values with their neighbors. This effect is often used to reduce noise and detail, creating a softened appearance.</p>\n<p>The blurring process involves using a convolution kernel (or filter) that averages the pixel values in a neighborhood. A common kernel used for blurring is the Gaussian kernel or a simple box blur kernel.</p>\n<h3>Blurring with a Kernel</h3>\n<p>A simple 3x3 box blur kernel can be used to average the pixel values. The new value of a pixel is calculated by averaging its value with the values of its neighboring pixels.</p>\n<p>An example of a box blur kernel is:</p>\n<p>\\[\n\\begin{bmatrix}\n\\frac{1}{9} & \\frac{1}{9} & \\frac{1}{9} \\\\\n\\frac{1}{9} & \\frac{1}{9} & \\frac{1}{9} \\\\\n\\frac{1}{9} & \\frac{1}{9} & \\frac{1}{9}\n\\end{bmatrix}\n\\]</p>\n<p>This kernel averages the values of the pixel and its eight neighbors.</p>\n<h3>Example Calculation</h3>\n<p>Consider a pixel \\( P \\) and its 3x3 neighborhood:</p>\n<p>\\[\n\\begin{bmatrix}\nP_{11} & P_{12} & P_{13} \\\\\nP_{21} & P & P_{23} \\\\\nP_{31} & P_{32} & P_{33}\n\\end{bmatrix}\n\\]</p>\n<p>The new value of pixel \\( P' \\) is calculated as:</p>\n<p>\\[\nP' = \\frac{1}{9} (P_{11} + P_{12} + P_{13} + P_{21} + P + P_{23} + P_{31} + P_{32} + P_{33})\n\\]</p>\n<h3>Applying the Kernel to the Image</h3>\n<p>The blurring effect is applied to the entire image by convolving the blur kernel with the image. This involves moving the kernel over each pixel in the image, computing the new pixel values, and replacing the old values with the new blurred values.</p>\n<p>For a more sophisticated blur effect, a Gaussian blur kernel can be used. A Gaussian blur kernel applies a weighted average where the central pixel has more influence than the surrounding pixels.</p>\n<p>An example of a 3x3 Gaussian blur kernel is:</p>\n<p>\\[\n\\begin{bmatrix}\n\\frac{1}{16} & \\frac{2}{16} & \\frac{1}{16} \\\\\n\\frac{2}{16} & \\frac{4}{16} & \\frac{2}{16} \\\\\n\\frac{1}{16} & \\frac{2}{16} & \\frac{1}{16}\n\\end{bmatrix}\n\\]</p>\n<p>Blurring an image reduces its sharpness and detail, resulting in a smooth and softened appearance. The process involves averaging pixel values to diminish the prominence of edges and noise.</p>",
  "type": "image",
  "operation": "effect"
}