Image Emboss Effect Online

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How to use this tool to Image Emboss Effect 🤔

Click 👆 on the Choose File(s) button and choose input image files, or you may drag and drop the image files to the Drop area. You may choose one image 🌁 or multiple images 🌃 🌄 🎇. The chosen images are displayed with size information in the input section.
You may change the conversion parameters like quality 🎛, background color, etc., using the sliders, or color input buttons.
Now you can click on the Submit button. This is where the ⛄ magic happens. Your images are sent ➚ to the server for the specified Image Emboss Effect operation. This all happens in a lightening speed ⚡.
Once the input images are transformed ✅, they appear in the download section.
You may click 👆 on the big Download button to download ↓ all your transformed images.
There is also a link 🔗 which you can Copy and share it using which you can download the resulting images.

Disclaimer:Please be aware that due to limited server storage, converted images will be automatically purged over time for optimal server performance.

Image Emboss Effect

The emboss image effect gives an image a three-dimensional, relief-like appearance by highlighting edges and creating shadows. This effect emphasizes the edges in the image, making it look as though the features are raised or carved into the surface.

The embossing process involves using a convolution kernel (or filter) that calculates the gradient of pixel values, which helps in highlighting the edges.

Embossing with a Kernel

An embossing kernel emphasizes the differences between adjacent pixels to create a raised effect. A common 3x3 embossing kernel is:

\[ \begin{bmatrix} -2 & -1 & 0 \\ -1 & 1 & 1 \\ 0 & 1 & 2 \end{bmatrix} \]

This kernel highlights the edges by subtracting the pixel values on one side and adding on the other, creating a shadow and highlight effect.

Example Calculation

Consider a pixel \( P \) and its 3x3 neighborhood:

\[ \begin{bmatrix} P_{11} & P_{12} & P_{13} \\ P_{21} & P & P_{23} \\ P_{31} & P_{32} & P_{33} \end{bmatrix} \]

The new value of pixel \( P' \) is calculated as:

\[ P' = (-2 \cdot P_{11}) + (-1 \cdot P_{12}) + (0 \cdot P_{13}) + (-1 \cdot P_{21}) + (1 \cdot P) + (1 \cdot P_{23}) + (0 \cdot P_{31}) + (1 \cdot P_{32}) + (2 \cdot P_{33}) \]

This calculation emphasizes the edges by creating a contrast between the pixel and its neighbors.

Applying the Kernel to the Image

The emboss effect is applied to the entire image by convolving the embossing 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 embossed values.

Embossing an image enhances its edges, giving it a three-dimensional, textured appearance. The process involves adjusting the pixel values based on their neighbors to create shadows and highlights that mimic a relief effect.

{ "operation": "emboss", "title": "Image Emboss Effect", "description": "You can use this Image Emboss Effect tool, to apply emboss effect to image(s). You can do for bulk number of images in one go.", "multiple": true, "controls": [], "content": "<h2>Image Emboss Effect</h2>\n<p>The emboss image effect gives an image a three-dimensional, relief-like appearance by highlighting edges and creating shadows. This effect emphasizes the edges in the image, making it look as though the features are raised or carved into the surface.</p>\n<p>The embossing process involves using a convolution kernel (or filter) that calculates the gradient of pixel values, which helps in highlighting the edges.</p>\n<h3>Embossing with a Kernel</h3>\n<p>An embossing kernel emphasizes the differences between adjacent pixels to create a raised effect. A common 3x3 embossing kernel is:</p>\n<p>\\[\n\\begin{bmatrix}\n-2 & -1 & 0 \\\\\n-1 & 1 & 1 \\\\\n0 & 1 & 2\n\\end{bmatrix}\n\\]</p>\n<p>This kernel highlights the edges by subtracting the pixel values on one side and adding on the other, creating a shadow and highlight effect.</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' = (-2 \\cdot P_{11}) + (-1 \\cdot P_{12}) + (0 \\cdot P_{13}) + (-1 \\cdot P_{21}) + (1 \\cdot P) + (1 \\cdot P_{23}) + (0 \\cdot P_{31}) + (1 \\cdot P_{32}) + (2 \\cdot P_{33})\n\\]</p>\n<p>This calculation emphasizes the edges by creating a contrast between the pixel and its neighbors.</p>\n<h3>Applying the Kernel to the Image</h3>\n<p>The emboss effect is applied to the entire image by convolving the embossing 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 embossed values.</p>\n<p>Embossing an image enhances its edges, giving it a three-dimensional, textured appearance. The process involves adjusting the pixel values based on their neighbors to create shadows and highlights that mimic a relief effect.</p>" }